fix: temporary patch on broken sum with empty axis

src/boost_histogram/_core/accumulators.pyi

@@ -1,4 +1,4 @@
-from typing import Any, Tuple, TypeVar
+from typing import Any, Tuple, TypeVar, overload
 
 from numpy.typing import ArrayLike
 
@@ -14,7 +14,12 @@ class _BaseAccumulator:
  def _ipython_key_completions_(self) -> Tuple[str, ...]: ...
 
 class WeightedSum(_BaseAccumulator):
- def __init__(self, value: float | None, variance: float | None) -> None: ...
+ @overload
+ def __init__(self) -> None: ...
+ @overload
+ def __init__(self, value: float) -> None: ...
+ @overload
+ def __init__(self, value: float, variance: float) -> None: ...
  @property
  def value(self) -> float: ...
  @property
@@ -29,7 +34,10 @@ class WeightedSum(_BaseAccumulator):
  def __setitem__(self, key: str, value: float) -> None: ...
 
 class Sum(_BaseAccumulator):
- def __init__(self, value: float | None) -> None: ...
+ @overload
+ def __init__(self) -> None: ...
+ @overload
+ def __init__(self, value: float) -> None: ...
  @property
  def value(self) -> float: ...
  def __iadd__(self: T, arg0: float) -> T: ...
@@ -40,6 +48,9 @@ class Sum(_BaseAccumulator):
  def _large(self) -> float: ...
 
 class WeightedMean(_BaseAccumulator):
+ @overload
+ def __init__(self) -> None: ...
+ @overload
  def __init__(
  self,
  sum_of_weights: float,
@@ -73,6 +84,9 @@ class WeightedMean(_BaseAccumulator):
  def __setitem__(self, key: str, value: float) -> None: ...
 
 class Mean(_BaseAccumulator):
+ @overload
+ def __init__(self) -> None: ...
+ @overload
  def __init__(self, count: float, value: float, variance: float) -> None: ...
  @property
  def count(self) -> float: ...

src/boost_histogram/_internal/hist.py

@@ -743,6 +743,9 @@ def sum(self, flow: bool = False) -> Union[float, Accumulator]:
  """
  Compute the sum over the histogram bins (optionally including the flow bins).
  """
+ if any(x == 0 for x in (self.axes.extent if flow else self.axes.size)):
+ return self._storage_type.accumulator()
+
  return self._hist.sum(flow) # type: ignore[no-any-return]
 
  @property

src/boost_histogram/_internal/storage.py

@@ -1,5 +1,8 @@
+from typing import ClassVar, Type, Union
+
 import boost_histogram
 
+from .._core import accumulators
 from .._core import storage as store
 from .utils import set_module
 
@@ -15,37 +18,47 @@ def __init_subclass__(cls, *, family: object) -> None:
  def __repr__(self) -> str:
  return f"{self.__class__.__name__}()"
 
+ accumulator: ClassVar[
+ Union[
+ Type[int],
+ Type[float],
+ Type[accumulators.WeightedMean],
+ Type[accumulators.WeightedSum],
+ Type[accumulators.Mean],
+ ]
+ ]
+
 
 @set_module("boost_histogram.storage")
 class Int64(store.int64, Storage, family=boost_histogram):
- pass
+ accumulator = int
 
 
 @set_module("boost_histogram.storage")
 class Double(store.double, Storage, family=boost_histogram):
- pass
+ accumulator = float
 
 
 @set_module("boost_histogram.storage")
 class AtomicInt64(store.atomic_int64, Storage, family=boost_histogram):
- pass
+ accumulator = int
 
 
 @set_module("boost_histogram.storage")
 class Unlimited(store.unlimited, Storage, family=boost_histogram):
- pass
+ accumulator = float
 
 
 @set_module("boost_histogram.storage")
 class Weight(store.weight, Storage, family=boost_histogram):
- pass
+ accumulator = accumulators.WeightedSum
 
 
 @set_module("boost_histogram.storage")
 class Mean(store.mean, Storage, family=boost_histogram):
- pass
+ accumulator = accumulators.Mean
 
 
 @set_module("boost_histogram.storage")
 class WeightedMean(store.weighted_mean, Storage, family=boost_histogram):
- pass
+ accumulator = accumulators.WeightedMean

tests/test_storage.py

@@ -277,3 +277,25 @@ def test_UHI_variance_counts():
  h.fill(0.5, sample=[1], weight=[0.5])
  h.fill(0.5, sample=[1], weight=[0.5])
  assert not math.isnan(h.variances()[0])
+
+
+@pytest.mark.parametrize(
+ "storage",
+ [
+ bh.storage.Int64,
+ bh.storage.Double,
+ bh.storage.AtomicInt64,
+ bh.storage.Unlimited,
+ bh.storage.Weight,
+ bh.storage.Mean,
+ bh.storage.WeightedMean,
+ ],
+)
+def test_empty_axis_histogram(storage):
+ h2d = bh.Histogram(
+ bh.axis.Regular(10, 0, 10),
+ bh.axis.StrCategory([], growth=True),
+ storage=storage(),
+ )
+ assert h2d.sum() == h2d._storage_type.accumulator()
+ assert h2d.sum(flow=True) == h2d._storage_type.accumulator()