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https://github.com/wassname/catalyst.git
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Trying to fix an issue with periodical bars
This commit is contained in:
fredfortier
@@ -49,7 +49,7 @@ from catalyst.utils.input_validation import error_keywords, ensure_upper_case, \
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expect_types
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from catalyst.utils.preprocess import preprocess
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log = logbook.Logger("ExchangeTradingAlgorithm")
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log = logbook.Logger('exchange_algorithm')
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class ExchangeAlgorithmExecutor(AlgorithmSimulator):
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@@ -59,6 +59,8 @@ class ExchangeAlgorithmExecutor(AlgorithmSimulator):
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class ExchangeTradingAlgorithmBase(TradingAlgorithm):
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def __init__(self, *args, **kwargs):
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self.exchanges = kwargs.pop('exchanges', None)
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super(ExchangeTradingAlgorithmBase, self).__init__(*args, **kwargs)
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@api_method
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@@ -106,10 +108,83 @@ class ExchangeTradingAlgorithmBase(TradingAlgorithm):
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as_of_date=_lookup_date
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)
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def prepare_period_stats(self, start_dt, end_dt):
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"""
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Creates a dictionary representing the state of the tracker.
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class ExchangeTradingAlgorithm(ExchangeTradingAlgorithmBase):
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I rewrote this in an attempt to better control the stats.
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I don't want things to happen magically through complex logic
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pertaining to backtesting.
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"""
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tracker = self.perf_tracker
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period = tracker.todays_performance
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pos_stats = period.position_tracker.stats()
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period_stats = calc_period_stats(pos_stats, period.ending_cash)
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stats = dict(
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period_start=tracker.period_start,
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period_end=tracker.period_end,
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capital_base=tracker.capital_base,
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progress=tracker.progress,
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ending_value=period.ending_value,
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ending_exposure=period.ending_exposure,
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capital_used=period.cash_flow,
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starting_value=period.starting_value,
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starting_exposure=period.starting_exposure,
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starting_cash=period.starting_cash,
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ending_cash=period.ending_cash,
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portfolio_value=period.ending_cash + period.ending_value,
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pnl=period.pnl,
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returns=period.returns,
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period_open=period.period_open,
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period_close=period.period_close,
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gross_leverage=period_stats.gross_leverage,
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net_leverage=period_stats.net_leverage,
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short_exposure=pos_stats.short_exposure,
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long_exposure=pos_stats.long_exposure,
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short_value=pos_stats.short_value,
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long_value=pos_stats.long_value,
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longs_count=pos_stats.longs_count,
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shorts_count=pos_stats.shorts_count,
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)
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# Merging cumulative risk
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stats.update(tracker.cumulative_risk_metrics.to_dict())
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# Merging latest recorded variables
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stats.update(self.recorded_vars)
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stats['positions'] = period.position_tracker.get_positions_list()
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# we want the key to be absent, not just empty
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# Only include transactions for given dt
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stats['transactions'] = dict()
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for date in period.processed_transactions:
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if start_dt <= date < end_dt:
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stats['transactions'][date] = \
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period.processed_transactions[date]
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stats['orders'] = dict()
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for date in period.orders_by_modified:
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if start_dt <= date < end_dt:
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stats['orders'][date] = \
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period.orders_by_modified[date]
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return stats
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class ExchangeTradingAlgorithmBacktest(ExchangeTradingAlgorithmBase):
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def __init__(self, *args, **kwargs):
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super(ExchangeTradingAlgorithmBacktest, self).__init__(*args, **kwargs)
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log.info('initialized trading algorithm in backtest mode')
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class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
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def __init__(self, *args, **kwargs):
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self.exchanges = kwargs.pop('exchanges', None)
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self.algo_namespace = kwargs.pop('algo_namespace', None)
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self.live_graph = kwargs.pop('live_graph', None)
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@@ -134,13 +209,13 @@ class ExchangeTradingAlgorithm(ExchangeTradingAlgorithmBase):
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self.stats_minutes = 5
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super(ExchangeTradingAlgorithm, self).__init__(*args, **kwargs)
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super(ExchangeTradingAlgorithmLive, self).__init__(*args, **kwargs)
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# TODO: fix precision before re-enabling
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# self._create_minute_writer()
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signal.signal(signal.SIGINT, self.signal_handler)
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log.info('exchange trading algorithm successfully initialized')
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log.info('initialized trading algorithm in live mode')
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def _create_minute_writer(self):
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root = get_exchange_minute_writer_root(self.exchange.name)
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@@ -360,73 +435,6 @@ class ExchangeTradingAlgorithm(ExchangeTradingAlgorithmBase):
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save_algo_df(self.algo_namespace, 'exposure_stats',
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self.exposure_stats)
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def prepare_period_stats(self, start_dt, end_dt):
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"""
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Creates a dictionary representing the state of the tracker.
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I rewrote this in an attempt to better control the stats.
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I don't want things to happen magically through complex logic
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pertaining to backtesting.
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"""
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tracker = self.perf_tracker
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period = tracker.todays_performance
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pos_stats = period.position_tracker.stats()
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period_stats = calc_period_stats(pos_stats, period.ending_cash)
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stats = dict(
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period_start=tracker.period_start,
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period_end=tracker.period_end,
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capital_base=tracker.capital_base,
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progress=tracker.progress,
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ending_value=period.ending_value,
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ending_exposure=period.ending_exposure,
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capital_used=period.cash_flow,
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starting_value=period.starting_value,
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starting_exposure=period.starting_exposure,
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starting_cash=period.starting_cash,
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ending_cash=period.ending_cash,
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portfolio_value=period.ending_cash + period.ending_value,
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pnl=period.pnl,
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returns=period.returns,
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period_open=period.period_open,
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period_close=period.period_close,
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gross_leverage=period_stats.gross_leverage,
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net_leverage=period_stats.net_leverage,
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short_exposure=pos_stats.short_exposure,
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long_exposure=pos_stats.long_exposure,
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short_value=pos_stats.short_value,
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long_value=pos_stats.long_value,
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longs_count=pos_stats.longs_count,
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shorts_count=pos_stats.shorts_count,
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)
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# Merging cumulative risk
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stats.update(tracker.cumulative_risk_metrics.to_dict())
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# Merging latest recorded variables
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stats.update(self.recorded_vars)
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stats['positions'] = period.position_tracker.get_positions_list()
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# we want the key to be absent, not just empty
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# Only include transactions for given dt
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stats['transactions'] = dict()
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for date in period.processed_transactions:
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if start_dt <= date < end_dt:
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stats['transactions'][date] = \
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period.processed_transactions[date]
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stats['orders'] = dict()
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for date in period.orders_by_modified:
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if start_dt <= date < end_dt:
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stats['orders'][date] = \
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period.orders_by_modified[date]
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return stats
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def handle_data(self, data):
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if not self.is_running:
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return
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