def resolve(self, asset_finder, start_date, end_date):
"""
Resolve inputs into values to be passed to TradingAlgorithm.
Returns a pair of ``(benchmark_sid, benchmark_returns)`` with at most
one non-None value. Both values may be None if no benchmark source has
been configured.
Parameters
----------
asset_finder : zipline.assets.AssetFinder
Asset finder for the algorithm to be run.
start_date : pd.Timestamp
Start date of the algorithm to be run.
end_date : pd.Timestamp
End date of the algorithm to be run.
Returns
-------
benchmark_sid : int
Sid to use as benchmark.
benchmark_returns : pd.Series
Series of returns to use as benchmark.
"""
if self.benchmark_returns is not None:
benchmark_sid = None
benchmark_returns = self.benchmark_returns
elif self.benchmark_file is not None:
benchmark_sid = None
benchmark_returns = get_benchmark_returns_from_file(
self.benchmark_file, )
elif self.benchmark_sid is not None:
benchmark_sid = self.benchmark_sid
benchmark_returns = None
elif self.no_benchmark:
benchmark_sid = None
benchmark_returns = self._zero_benchmark_returns(
start_date=start_date,
end_date=end_date,
)
else:
benchmark_sid = None
benchmark_returns = None
return benchmark_sid, benchmark_returns
def resolve(self, asset_finder, start_date, end_date):
"""
Resolve inputs into values to be passed to TradingAlgorithm.
Returns a pair of ``(benchmark_sid, benchmark_returns)`` with at most
one non-None value. Both values may be None if no benchmark source has
been configured.
Parameters
----------
asset_finder : zipline.assets.AssetFinder
Asset finder for the algorithm to be run.
start_date : pd.Timestamp
Start date of the algorithm to be run.
end_date : pd.Timestamp
End date of the algorithm to be run.
Returns
-------
benchmark_sid : int
Sid to use as benchmark.
benchmark_returns : pd.Series
Series of returns to use as benchmark.
"""
if self.benchmark_returns is not None:
benchmark_sid = None
benchmark_returns = self.benchmark_returns
elif self.benchmark_file is not None:
benchmark_sid = None
benchmark_returns = get_benchmark_returns_from_file(
self.benchmark_file, )
elif self.benchmark_sid is not None:
benchmark_sid = self.benchmark_sid
benchmark_returns = None
elif self.benchmark_symbol is not None:
try:
asset = asset_finder.lookup_symbol(
self.benchmark_symbol,
as_of_date=end_date,
)
benchmark_sid = asset.sid
benchmark_returns = None
except SymbolNotFound:
raise _RunAlgoError(
"Symbol %s as a benchmark not found in this bundle.")
else:
if not self.no_benchmark:
log.warn("No benchmark configured. "
"Assuming algorithm calls set_benchmark.")
log.warn(
"Pass --benchmark-sid, --benchmark-symbol, or"
" --benchmark-file to set a source of benchmark returns.")
log.warn(
"Pass --no-benchmark to use a dummy benchmark "
"of zero returns.", )
benchmark_sid = None
benchmark_returns = None
else:
benchmark_sid = None
benchmark_returns = self._zero_benchmark_returns(
start_date=start_date,
end_date=end_date,
)
return benchmark_sid, benchmark_returns