def test_compare_against_oneoff_calculation(self):
rw = np.cumsum(np.random.normal(0, 2, 1000)) + 100
close = DataSeries(time_series=ModelFactory.build_time_series(
series_id="close"))
close.start(self.app_context)
t = 1
sma = SMA(inputs=close, input_keys='close', length=50)
sma.start(self.app_context)
result = []
for x in rw:
close.add(timestamp=t, data={"close": x})
result.append(sma.now('value'))
t = t + 3
result = np.array(result)
# either apply or direct call is equivalent
target = close.apply('close',
start=None,
end=None,
func=talib.SMA,
timeperiod=50)
# target = talib.SMA(np.array(close.get_series('close')), timeperiod=50)
result[np.isnan(result)] = 0
target[np.isnan(target)] = 0
try:
np.testing.assert_almost_equal(target, result, 5)
except AssertionError as e:
self.fail(e.message)
def test_get_by_idx(self):
ts = DataSeriesTest.factory.build_time_series(series_id="test", keys=["timestamp", "v1", "v2"])
series = DataSeries(time_series=ts)
series.add(data={"timestamp": 0, "v1": 2})
series.add(data={"timestamp": 1, "v1": 2.4})
series.add(data={"timestamp": 1, "v2": 3.0})
# index and key
self.assertEqual(2, series.get_by_idx(idx=0, keys="v1"))
self.assertEqual(0.0, series.get_by_idx(idx=0, keys="v2"))
self.assertEqual(2.4, series.get_by_idx(idx=1, keys="v1"))
self.assertEqual(3.0, series.get_by_idx(idx=1, keys="v2"))
# index only
self.assertEqual({"timestamp": 0, "v1": 2, "v2": 0.0}, series.get_by_idx(idx=0))
self.assertEqual({"timestamp": 1, "v1": 2.4, "v2": 3.0}, series.get_by_idx(idx=1))
# test index slice
series2 = self.create_series_by_list(range(100))
sliced = series2.get_by_idx(keys='v1', idx=slice(-10, None, None))
self.assertEqual(len(sliced), 10)
endPoint = series2.get_by_idx(keys='v1', idx=slice(-1, None, None))
self.assertEqual(endPoint[0], 99)
class PnlAnalyzer(Analyzer):
Pnl = "Pnl"
def __init__(self, portfolio, state):
self.portfolio = portfolio
self.state = state
self.series = DataSeries(time_series=self.state.pnl.series)
def update(self, timestamp: int, total_equity: float):
performance_series = self.portfolio.performance.series
if self.series.size() >= 2:
self.state.pnl.last_pnl = performance_series.get_by_idx(-1, PerformanceAnalyzer.TotalEquity) - \
performance_series.get_by_idx(-2, PerformanceAnalyzer.TotalEquity)
self.series.add(timestamp=timestamp, data={self.Pnl: self.state.pnl.last_pnl})
else:
self.state.pnl.last_pnl = 0
self.series.add(timestamp=timestamp, data={self.Pnl: self.state.pnl.last_pnl})
def get_result(self):
return {self.Pnl: self.state.pnl.last_pnl}
def get_series(self, keys=None):
keys = keys if keys else self.Pnl
return {self.Pnl: self.series.get_series(self.Pnl)}
def last_pnl(self) -> float:
return self.state.pnl.last_pnl
def __create_series(self):
close = DataSeries(time_series=TimeSeries())
t = 0
for idx, value in enumerate(self.values):
close.add(data={"timestamp": t, "v1": value, "v2": value})
t = t + 3
return close
def create_series_by_list(valuelist):
close = DataSeries(time_series=TimeSeries())
t = 0
for value in valuelist:
close.add(data={"timestamp": t, "v1": value})
t = t + 3
return close
def create_series_by_list(valuelist):
close = DataSeries(time_series=ModelFactory.build_time_series(
series_id="close"))
t = 1
for value in valuelist:
close.add(timestamp=t, data={"v1": value})
t = t + 3
return close
def test_get_data(self):
ts = DataSeriesTest.factory.build_time_series(series_id="test")
series = DataSeries(time_series=ts)
series.add(data={"timestamp": 1, "v1": 1, "v2": 1})
series.add(data={"timestamp": 2, "v1": 2, "v2": 2})
self.assertEqual([{"timestamp": 1, "v1": 1, "v2": 1},
{"timestamp": 2, "v1": 2, "v2": 2}], series.get_data())
def __create_plot(self):
series = DataSeries(time_series=TimeSeries())
t = 20170101
for idx, value in enumerate(self.values):
ts = datestr_to_unixtimemillis(t)
series.add(timestamp=ts, data={"value": value})
t = t + 1
values = series.get_series(["value"])
plot = TimeSeriesPlot(values)
return plot
def test_size(self):
ts = DataSeriesTest.factory.build_time_series(series_id="test")
series = DataSeries(time_series=ts)
self.assertEqual(0, series.size())
series.add(data={"timestamp": 0, "v1": 1})
self.assertEqual(1, series.size())
series.add(data={"timestamp": 1, "v1": 1})
self.assertEqual(2, series.size())
def create_random_walk_series():
close = DataSeries(time_series=TimeSeries())
t1 = 1
t = t1
w = np.random.normal(0, 1, 1000)
xs = 100 + np.cumsum(w)
for value in xs:
close.add(data={"timestamp": t, "v1": value, "v2": value})
t = t + 3
return close
def test_init_w_keys(self):
ts = DataSeriesTest.factory.build_time_series(series_id="test",
keys=["v1"])
series = DataSeries(time_series=ts)
series.add(data={"timestamp": 0, "v1": 1, "v2": 1})
result = series.get_data()
self.assertEqual(1, len(result))
self.assertTrue("v1" in result[0])
self.assertFalse("v2" in result[0])
def test_ago(self):
ts = DataSeriesTest.factory.build_time_series(series_id="test")
series = DataSeries(time_series=ts)
self.assertEqual(0.0, series.now())
series.add(data={"timestamp": 0, "v1": 1, "v2": 2})
self.assertEqual({"timestamp": 0, "v1": 1, "v2": 2}, series.ago(0))
series.add(data={"timestamp": 1, "v1": 1.2, "v2": 2.2})
self.assertEqual({"timestamp": 1, "v1": 1.2, "v2": 2.2}, series.ago(0))
self.assertEqual({"timestamp": 0, "v1": 1, "v2": 2}, series.ago(1))
series.add(data={"timestamp": 2, "v1": 1.3, "v2": 2.3})
self.assertEqual({"timestamp": 2, "v1": 1.3, "v2": 2.3}, series.ago(0))
self.assertEqual({"timestamp": 1, "v1": 1.2, "v2": 2.2}, series.ago(1))
self.assertEqual({"timestamp": 0, "v1": 1, "v2": 2}, series.ago(2))
series.add(data={"timestamp": 3, "v1": 1.4, "v2": 2.4})
self.assertEqual({"timestamp": 3, "v1": 1.4, "v2": 2.4}, series.ago(0))
self.assertEqual({"timestamp": 2, "v1": 1.3, "v2": 2.3}, series.ago(1))
self.assertEqual({"timestamp": 1, "v1": 1.2, "v2": 2.2}, series.ago(2))
self.assertEqual({"timestamp": 0, "v1": 1, "v2": 2}, series.ago(3))
self.assertEqual({"v1": 1.4, "v2": 2.4}, series.ago(0, ["v1", "v2"]))
self.assertEqual(1.4, series.ago(0, "v1"))
self.assertEqual(1.4, series.ago(0, ["v1"]))
def test_get_data_dict(self):
ts = DataSeriesTest.factory.build_time_series(series_id="test")
series = DataSeries(time_series=ts)
series.add(data={"timestamp": 1, "v1": 1, "v2": 1})
series.add(data={"timestamp": 2, "v1": 2, "v2": 2})
self.assertEqual({"timestamp": {1: 1, 2: 2},
"v1": {1: 1, 2: 2},
"v2": {1: 1, 2: 2}}, series.get_data_dict())
self.assertEqual({"v1": {1: 1, 2: 2}, "v2": {1: 1, 2: 2}},
series.get_data_dict(['v1', 'v2']))
self.assertEqual({1: 1, 2: 2}, series.get_data_dict('v1'))
def test_get_by_time(self):
ts = DataSeriesTest.factory.build_time_series(series_id="test", keys=["timestamp", "v1", "v2"])
series = DataSeries(time_series=ts)
# time and key
series.add(data={"timestamp": 0, "v1": 2})
series.add(data={"timestamp": 1, "v1": 2.4})
series.add(data={"timestamp": 1, "v2": 3.0})
self.assertEqual(2, series.get_by_time(time=0, keys="v1"))
self.assertEqual(0.0, series.get_by_time(time=0, keys="v2"))
self.assertEqual(2.4, series.get_by_time(time=1, keys="v1"))
self.assertEqual(3.0, series.get_by_time(time=1, keys="v2"))
# time only
self.assertEqual({"timestamp": 0, "v1": 2, "v2": 0.0}, series.get_by_time(time=0))
self.assertEqual({"timestamp": 1, "v1": 2.4, "v2": 3.0}, series.get_by_time(time=1))
class PerformanceAnalyzer(Analyzer):
Performance = "Performance"
StockValue = "stock_value"
Cash = "cash"
TotalEquity = "total_equity"
def __init__(self, portfolio, state):
self.portfolio = portfolio
self.state = state
self.series = DataSeries(time_series=self.state.performance.series)
def update(self, timestamp: int, total_equity: float):
self.state.performance.total_equity = total_equity
self.series.add(timestamp=timestamp,
data={
self.StockValue: self.state.stock_value,
self.Cash: self.state.cash,
self.TotalEquity: total_equity
})
def get_result(self):
return {
self.StockValue: self.state.stock_value,
self.Cash: self.state.cash,
self.TotalEquity: self.state.performance.total_equity
}
def get_series(self, keys=None):
keys = keys if keys else [self.StockValue, self.Cash, self.TotalEquity]
return self.series.get_series(keys)
def now(self, key):
return self.series.now(key)
def total_equity(self) -> float:
return self.state.performance.total_equity
def test_override_w_same_time(self):
ts = DataSeriesTest.factory.build_time_series(series_id="test", keys=["timestamp", "v1", "v2", "v3"])
series = DataSeries(time_series=ts)
series.add(data={"timestamp": 1, "v1": 2, "v2": 3})
self.assertEqual(1, series.size())
self.assertEqual(2, series.get_by_idx(0, "v1"))
self.assertEqual(2, series.get_by_time(1, "v1"))
self.assertEqual(3, series.get_by_idx(0, "v2"))
self.assertEqual(3, series.get_by_time(1, "v2"))
self.assertEqual(0.0, series.get_by_idx(0, "v3"))
self.assertEqual(0.0, series.get_by_time(1, "v3"))
series.add(data={"timestamp": 1, "v1": 2.4, "v2": 3.4, "v3": 1.1})
self.assertEqual(1, series.size())
self.assertEqual(2.4, series.get_by_idx(0, "v1"))
self.assertEqual(2.4, series.get_by_time(1, "v1"))
self.assertEqual(3.4, series.get_by_idx(0, "v2"))
self.assertEqual(3.4, series.get_by_time(1, "v2"))
self.assertEqual(1.1, series.get_by_idx(0, "v3"))
self.assertEqual(1.1, series.get_by_time(1, "v3"))
series.add(data={"timestamp": 2, "v1": 2.6, "v2": 3.6})
self.assertEqual(2, series.size())
self.assertEqual(2.4, series.get_by_idx(0, "v1"))
self.assertEqual(2.4, series.get_by_time(1, "v1"))
self.assertEqual(3.4, series.get_by_idx(0, "v2"))
self.assertEqual(3.4, series.get_by_time(1, "v2"))
self.assertEqual(1.1, series.get_by_idx(0, "v3"))
self.assertEqual(1.1, series.get_by_time(1, "v3"))
self.assertEqual(2.6, series.get_by_idx(1, "v1"))
self.assertEqual(2.6, series.get_by_time(2, "v1"))
self.assertEqual(3.6, series.get_by_idx(1, "v2"))
self.assertEqual(3.6, series.get_by_time(2, "v2"))
self.assertEqual(0.0, series.get_by_idx(1, "v3"))
self.assertEqual(0.0, series.get_by_time(2, "v3"))
def test_add(self):
ts = DataSeriesTest.factory.build_time_series(series_id="test")
series = DataSeries(time_series=ts)
self.assertTrue(len(series.get_data()) == 0)
series.add(data={"timestamp": 0, "v1": 1, "v2": 1})
series.add(data={"timestamp": 1, "v1": 2, "v2": 2})
self.assertEqual([{"timestamp": 0, "v1": 1, "v2": 1},
{"timestamp": 1, "v1": 2, "v2": 2}], series.get_data())
series.add(data={"timestamp": 1, "v1": 3, "v2": 3})
self.assertEqual([{"timestamp": 0, "v1": 1, "v2": 1},
{"timestamp": 1, "v1": 3, "v2": 3}], series.get_data())
series.add(data={"timestamp": 2, "v1": 4, "v2": 4})
self.assertEqual([{"timestamp": 0, "v1": 1, "v2": 1},
{"timestamp": 1, "v1": 3, "v2": 3},
{"timestamp": 2, "v1": 4, "v2": 4}], series.get_data())
class DrawDownAnalyzer(Analyzer):
DrawDown = "DrawDown"
DrawDownPct = "DrawDown%"
HighEquity = "HighEquity"
LowEquity = "LowEquity"
CurrentRunUp = "CurrentRunUp"
CurrentDrawDown = "CurrentDrawDown"
def __init__(self, portfolio, state):
self.portfolio = portfolio
self.state = state
self.series = DataSeries(time_series=self.state.drawdown.series)
def update(self, timestamp: int, total_equity: float):
if self.portfolio.performance.series.size() == 1:
self.state.drawdown.low_equity = total_equity
self.state.drawdown.high_equity = total_equity
else:
if total_equity > self.state.drawdown.high_equity:
self.state.drawdown.high_equity = total_equity
self.state.drawdown.low_equity = total_equity
self.state.drawdown.current_drawdown = 0
elif total_equity < self.state.drawdown.low_equity:
self.state.drawdown.low_equity = total_equity
self.state.drawdown.current_run_up = 0
elif total_equity > self.state.drawdown.low_equity and total_equity < self.state.drawdown.high_equity:
self.state.drawdown.current_drawdown = 1 - total_equity / self.state.drawdown.high_equity
self.state.drawdown.current_run_up = total_equity / self.state.drawdown.low_equity - 1
if self.portfolio.performance.series.size() >= 2:
self.state.drawdown.last_drawdown = total_equity - self.state.drawdown.high_equity
if self.state.drawdown.high_equity != 0:
self.state.drawdown.last_drawdown_pct = abs(
self.state.drawdown.last_drawdown /
self.state.drawdown.high_equity)
self.series.add(timestamp=timestamp,
data={
self.DrawDown:
self.state.drawdown.last_drawdown,
self.DrawDownPct:
self.state.drawdown.last_drawdown_pct
})
def get_result(self):
return {
self.DrawDown: self.state.drawdown.last_drawdown,
self.DrawDownPct: self.state.drawdown.last_drawdown_pct,
self.HighEquity: self.state.drawdown.high_equity,
self.LowEquity: self.state.drawdown.low_equity,
self.CurrentRunUp: self.state.drawdown.current_run_up,
self.CurrentDrawDown: self.state.drawdown.current_drawdown
}
def get_series(self, keys=None):
keys = keys if keys else [self.DrawDown, self.DrawDownPct]
return self.series.get_series(keys)
def last_drawdown(self) -> float:
return self.state.drawdown.last_drawdown
def last_drawdown_pct(self) -> float:
return self.state.drawdown.last_drawdown_pct
def high_equity(self) -> float:
return self.state.drawdown.high_equity
def low_equity(self) -> float:
return self.state.drawdown.low_equity
def current_run_up(self) -> float:
return self.state.drawdown.current_run_up
def current_drawdown(self) -> float:
return self.state.drawdown.current_drawdown
class BarAggregatorTest(TestCase):
class DummyEventBus:
def __init__(self):
self.items = []
def reset(self):
self.items = []
def on_next(self, item):
self.items.append(item)
def setUp(self):
self.time = 9000000000
self.simluation_clock = SimulationClock()
self.simluation_clock.reset()
self.simluation_clock.update_time(self.time)
self.input = DataSeries(time_series=TimeSeries())
self.event_bus = BarAggregatorTest.DummyEventBus()
def update(self, input, data):
self.simluation_clock.update_time(data.timestamp)
dict_data = {k : y for k, y in protobuf_to_dict(data).items() if isinstance(y, (int, float))}
self.input.add(timestamp=data.timestamp, data=dict_data)
def test_time_bar_from_trade(self):
agg = BarAggregator(data_bus=self.event_bus, clock=self.simluation_clock, inst_id="1", input=self.input)
agg.start(None)
self.assertEqual(0, len(self.event_bus.items))
self.time += 10000
t = ModelFactory.build_trade(timestamp=self.time, inst_id="1", price=20, size=200)
self.update(self.input, t)
self.assertEqual(1, agg.count())
self.assertTrue(len(self.event_bus.items) == 0)
# expect get a aggregated bar at 9000059999
self.time += 49999
t = ModelFactory.build_trade(timestamp=self.time, inst_id="1", price=10, size=200)
self.update(self.input, t)
items = self.event_bus.items
self.assertEqual(1, len(items))
self.assertEqual(0, agg.count())
self.assertEqual(
ModelFactory.build_bar(inst_id="1", begin_time=9000000000, timestamp=9000059999, type=Bar.Time, size=60, open=20, high=20, low=10,
close=10, vol=400), items[0])
def test_time_bar_from_bid(self):
agg = BarAggregator(data_bus=self.event_bus, clock=self.simluation_clock, inst_id="1", input=self.input,
input_type=BarAggregationRequest.Bid)
agg.start()
self.assertEqual(0, len(self.event_bus.items))
self.time += 10000
t = ModelFactory.build_quote(timestamp=self.time, inst_id="1", bid=30, bid_size=100)
self.update(self.input, t)
self.assertEqual(1, agg.count())
self.assertTrue(len(self.event_bus.items) == 0)
self.time += 10000
t = ModelFactory.build_quote(timestamp=self.time, inst_id="1", bid=10, bid_size=200)
self.update(self.input, t)
self.assertEqual(2, agg.count())
self.assertTrue(len(self.event_bus.items) == 0)
self.time += 10000
t = ModelFactory.build_quote(timestamp=self.time, inst_id="1", bid=70, bid_size=300)
self.update(self.input, t)
self.assertEqual(3, agg.count())
self.assertTrue(len(self.event_bus.items) == 0)
self.time += 29998
t = ModelFactory.build_quote(timestamp=self.time, inst_id="1", bid=50, bid_size=400)
self.update(self.input, t)
self.assertEqual(4, agg.count())
self.assertTrue(len(self.event_bus.items) == 0)
self.time += 3
self.simluation_clock.update_time(self.time)
items = self.event_bus.items
self.assertEqual(1, len(items))
self.assertEqual(0, agg.count())
self.assertEqual(
ModelFactory.build_bar(inst_id="1", begin_time=9000000000, timestamp=9000059999, type=Bar.Time, size=60, open=30, high=70, low=10,
close=50, vol=1000, adj_close=0), items[0])
def test_time_bar_from_ask(self):
agg = BarAggregator(data_bus=self.event_bus, clock=self.simluation_clock, inst_id="1", input=self.input,
input_type=BarAggregationRequest.Ask)
agg.start()
self.assertEqual(0, len(self.event_bus.items))
self.time += 10000
t = ModelFactory.build_quote(timestamp=self.time, inst_id="1", ask=30, ask_size=100)
self.update(self.input, t)
self.assertEqual(1, agg.count())
self.assertTrue(len(self.event_bus.items) == 0)
self.time += 60000
t = ModelFactory.build_quote(timestamp=self.time, inst_id="1", ask=70, ask_size=300)
self.update(self.input, t)
items = self.event_bus.items
self.assertEqual(1, len(items))
self.assertEqual(1, agg.count())
self.assertEqual(
ModelFactory.build_bar(inst_id="1", begin_time=9000000000, timestamp=9000059999, type=Bar.Time, size=60, open=30, high=30, low=30,
close=30, vol=100, adj_close=0), items[0])
self.event_bus.reset()
self.time += 49999
t = ModelFactory.build_quote(timestamp=self.time, inst_id="1", ask=20, ask_size=100)
self.update(self.input, t)
items = self.event_bus.items
self.assertEqual(1, len(items))
self.assertEqual(0, agg.count())
self.assertEqual(
ModelFactory.build_bar(inst_id="1", begin_time=9000060000, timestamp=9000119999, type=Bar.Time, size=60, open=70, high=70, low=20,
close=20, vol=400, adj_close=0), items[0])
def test_time_bar_from_bidask(self):
agg = BarAggregator(data_bus=self.event_bus, clock=self.simluation_clock, inst_id="1", input=self.input,
input_type=BarAggregationRequest.BidAsk)
agg.start()
self.assertEqual(0, len(self.event_bus.items))
self.time += 10000
t = ModelFactory.build_quote(timestamp=self.time, inst_id="1", ask=30, ask_size=100, bid=0, bid_size=200)
self.update(self.input, t)
self.assertEqual(1, agg.count())
self.assertTrue(len(self.event_bus.items) == 0)
self.time += 10000
t = ModelFactory.build_quote(timestamp=self.time, inst_id="1", ask=20, ask_size=150, bid=10, bid_size=0)
self.update(self.input, t)
self.assertEqual(2, agg.count())
self.assertTrue(len(self.event_bus.items) == 0)
self.time += 39999
t = ModelFactory.build_quote(timestamp=self.time, inst_id="1", ask=70, ask_size=300, bid=80, bid_size=10)
self.update(self.input, t)
items = self.event_bus.items
self.assertEqual(1, len(items))
self.assertEqual(0, agg.count())
self.assertEqual(
ModelFactory.build_bar(inst_id="1", begin_time=9000000000, timestamp=9000059999, type=Bar.Time, size=60, open=30, high=80, low=20,
close=80, vol=260, adj_close=0), items[0])
def test_time_bar_from_mid(self):
agg = BarAggregator(data_bus=self.event_bus, clock=self.simluation_clock, inst_id="1", input=self.input,
input_type=BarAggregationRequest.Middle)
agg.start(None)
self.assertEqual(0, len(self.event_bus.items))
self.time += 59999
t = ModelFactory.build_quote(timestamp=self.time, inst_id="1", ask=30, ask_size=100, bid=18, bid_size=200)
self.update(self.input, t)
items = self.event_bus.items
self.assertEqual(1, len(items))
self.assertEqual(0, agg.count())
self.assertEqual(
ModelFactory.build_bar(inst_id="1", begin_time=9000000000, timestamp=9000059999, type=Bar.Time, size=60, open=24, high=24, low=24,
close=24, vol=150, adj_close=0), items[0])
def test_tick_bar_from_trade(self):
agg = BarAggregator(data_bus=self.event_bus, clock=self.simluation_clock, inst_id="1", input=self.input,
output_bar_type=Bar.Tick, output_size=3)
agg.start()
self.assertEqual(0, len(self.event_bus.items))
self.time += 60000
t = ModelFactory.build_trade(timestamp=self.time, inst_id="1", price=20, size=200)
self.update(self.input, t)
self.assertEqual(1, agg.count())
self.assertTrue(len(self.event_bus.items) == 0)
self.time += 60000
t = ModelFactory.build_trade(timestamp=self.time, inst_id="1", price=80, size=100)
self.update(self.input, t)
self.assertEqual(2, agg.count())
self.assertTrue(len(self.event_bus.items) == 0)
self.time += 60000
t = ModelFactory.build_trade(timestamp=self.time, inst_id="1", price=10, size=200)
self.update(self.input, t)
items = self.event_bus.items
self.assertEqual(1, len(items))
self.assertEqual(0, agg.count())
self.assertEqual(
ModelFactory.build_bar(inst_id="1", begin_time=9000060000, timestamp=9000180000, type=Bar.Tick, size=3, open=20, high=80,
low=10,
close=10, vol=500, adj_close=0), items[0])
def test_vol_bar_from_trade(self):
agg = BarAggregator(data_bus=self.event_bus, clock=self.simluation_clock, inst_id="1", input=self.input,
output_bar_type=Bar.Volume, output_size=1000)
agg.start(None)
self.assertEqual(0, len(self.event_bus.items))
self.time += 60000
t = ModelFactory.build_trade(timestamp=self.time, inst_id="1", price=20, size=200)
self.update(self.input, t)
self.assertEqual(1, agg.count())
self.assertTrue(len(self.event_bus.items) == 0)
self.time += 60000
t = ModelFactory.build_trade(timestamp=self.time, inst_id="1", price=80, size=100)
self.update(self.input, t)
self.assertEqual(2, agg.count())
self.assertTrue(len(self.event_bus.items) == 0)
self.time += 60000
t = ModelFactory.build_trade(timestamp=self.time, inst_id="1", price=10, size=1000)
self.update(self.input, t)
items = self.event_bus.items
self.assertEqual(1, len(items))
self.assertEqual(1, agg.count())
self.assertEqual(
ModelFactory.build_bar(inst_id="1", begin_time=9000060000, timestamp=9000180000, type=Bar.Volume, size=1000, open=20,
high=80, low=10,
close=10, vol=1000, adj_close=0), items[0])
self.event_bus.reset()
self.time += 60000
t = ModelFactory.build_trade(timestamp=self.time, inst_id="1", price=50, size=2800)
self.update(self.input, t)
items = self.event_bus.items
self.assertEqual(3, len(items))
self.assertEqual(1, agg.count())
self.assertEqual(
ModelFactory.build_bar(inst_id="1", begin_time=9000180000, timestamp=9000240000, type=Bar.Volume, size=1000, open=10,
high=50, low=10,
close=50, vol=1000, adj_close=0), items[0])
self.assertEqual(
ModelFactory.build_bar(inst_id="1", begin_time=9000240000, timestamp=9000240000, type=Bar.Volume, size=1000, open=50,
high=50, low=50,
close=50, vol=1000, adj_close=0), items[1])
self.assertEqual(
ModelFactory.build_bar(inst_id="1", begin_time=9000240000, timestamp=9000240000, type=Bar.Volume, size=1000, open=50,
high=50, low=50,
close=50, vol=1000, adj_close=0), items[2])
self.event_bus.reset()
self.time += 60000
t = ModelFactory.build_trade(timestamp=self.time, inst_id="1", price=20, size=900)
self.update(self.input, t)
items = self.event_bus.items
self.assertEqual(1, len(items))
self.assertEqual(0, agg.count())
self.assertEqual(
ModelFactory.build_bar(inst_id="1", begin_time=9000240000, timestamp=9000300000, type=Bar.Volume, size=1000, open=50,
high=50, low=20,
close=20, vol=1000, adj_close=0), items[0])