def capture(self, factor_returns):
"""Capture ratio.
Args:
factor_returns (array_like): Benchmark return to compare returns against. Will broadcast."""
factor_returns = reshape_fns.broadcast_to(
reshape_fns.to_2d(factor_returns, raw=True),
reshape_fns.to_2d(self._obj, raw=True))
return self.wrap_reduced(nb.capture_nb(self.to_2d_array(), factor_returns, self.ann_factor))
def capture(self, benchmark_rets, wrap_kwargs=None):
"""Capture ratio.
Args:
benchmark_rets (array_like): Benchmark return to compare returns against. Will broadcast."""
benchmark_rets = reshape_fns.broadcast_to(
reshape_fns.to_2d(benchmark_rets, raw=True),
reshape_fns.to_2d(self._obj, raw=True))
wrap_kwargs = merge_dicts(dict(name_or_index='capture'), wrap_kwargs)
return self.wrapper.wrap_reduced(nb.capture_nb(
self.to_2d_array(), benchmark_rets, self.ann_factor
), **wrap_kwargs)
def capture(self,
benchmark_rets: tp.ArrayLike,
wrap_kwargs: tp.KwargsLike = None) -> tp.MaybeSeries:
"""Capture ratio.
Args:
benchmark_rets (array_like): Benchmark return to compare returns against. Will broadcast."""
benchmark_rets = broadcast_to(to_2d(benchmark_rets, raw=True),
to_2d(self._obj, raw=True))
result = nb.capture_nb(self.to_2d_array(), benchmark_rets,
self.ann_factor)
wrap_kwargs = merge_dicts(dict(name_or_index='capture'), wrap_kwargs)
return self.wrapper.wrap_reduced(result, **wrap_kwargs)