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MAINT: Allow the algorithm benchmark returns to be overrideable.

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So that test data can be well defined with a short list of benchmarks.

This could also lead to having more customizable benchmarks for
backtests.
This commit is contained in:
Eddie Hebert
2013-05-07 11:58:36 -04:00
parent e6c156c50b
commit aa54d0ae0e
1 changed files with 17 additions and 11 deletions
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zipline/algorithm.py
+17 -11
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@@ -98,6 +98,8 @@ class TradingAlgorithm(object):
self.logger = None
self.benchmark_return_source = None
# default components for transact
self.slippage = VolumeShareSlippage()
self.commission = PerShare()
@@ -161,15 +163,18 @@ class TradingAlgorithm(object):
processed by the zipline, and False for those that should be
skipped.
"""
benchmark_return_source = [
Event({'dt': ret.date,
'returns': ret.returns,
'type': zipline.protocol.DATASOURCE_TYPE.BENCHMARK,
'source_id': 'benchmarks'})
for ret in trading.environment.benchmark_returns
if ret.date.date() >= sim_params.period_start.date()
and ret.date.date() <= sim_params.period_end.date()
]
if self.benchmark_return_source is None:
benchmark_return_source = [
Event({'dt': ret.date,
'returns': ret.returns,
'type': zipline.protocol.DATASOURCE_TYPE.BENCHMARK,
'source_id': 'benchmarks'})
for ret in trading.environment.benchmark_returns
if ret.date.date() >= sim_params.period_start.date()
and ret.date.date() <= sim_params.period_end.date()
]
else:
benchmark_return_source = self.benchmark_return_source
date_sorted = date_sorted_sources(*self.sources)
@@ -197,7 +202,8 @@ class TradingAlgorithm(object):
processed by the zipline, and False for those that should be
skipped.
"""
self.data_gen = self._create_data_generator(source_filter, sim_params)
self.data_gen = self._create_data_generator(source_filter,
sim_params)
self.perf_tracker = PerformanceTracker(sim_params)
self.trading_client = AlgorithmSimulator(self, sim_params)
@@ -220,7 +226,7 @@ class TradingAlgorithm(object):
# TODO: make a new subclass, e.g. BatchAlgorithm, and move
# the run method to the subclass, and refactor to put the
# generator creation logic into get_generator.
def run(self, source, sim_params=None):
def run(self, source, sim_params=None, benchmark_return_source=None):
"""Run the algorithm.
:Arguments: