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Distributed weighted average() along tuple of axes: shape of weights to match shape of input #1037

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merged 6 commits into from
Jan 30, 2023
Merged

Distributed weighted average() along tuple of axes: shape of weights to match shape of input #1037

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240bc05
fix #351: Solution 1: enforce weights.shape = x.shape for tuple axis
Mystic-Slice Apr 3, 2022
116b9cb
Merge branch 'main' into RestrictWeightShape
ClaudiaComito Apr 25, 2022
2c5c7be
Merge branch 'helmholtz-analytics:main' into RestrictWeightShape
Mystic-Slice Oct 22, 2022
32dc258
Fixed tests to reflect changes
Mystic-Slice Oct 22, 2022
3fd0435
Merge branch 'main' into RestrictWeightShape
Mystic-Slice Oct 25, 2022
ba3cb59
Merge branch 'main' into RestrictWeightShape
Mystic-Slice Jan 27, 2023
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8 changes: 4 additions & 4 deletions heat/core/statistics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -206,14 +206,12 @@ def average(
Axis or axes along which to average ``x``. The default,
``axis=None``, will average over all of the elements of the input array.
If axis is negative it counts from the last to the first axis.
#TODO Issue #351: If axis is a tuple of ints, averaging is performed on all of the axes
specified in the tuple instead of a single axis or all the axes as
before.
weights : DNDarray, optional
An array of weights associated with the values in ``x``. Each value in
``x`` contributes to the average according to its associated weight.
The weights array can either be 1D (in which case its length must be
the size of ``x`` along the given axis) or of the same shape as ``x``.
Weighted average over tuple axis requires weights array to be of the same shape as ``x``.
If ``weights=None``, then all data in ``x`` are assumed to have a
weight equal to one, the result is equivalent to :func:`mean`.
returned : bool, optional
Expand Down Expand Up @@ -269,7 +267,9 @@ def average(
if axis is None:
raise TypeError("Axis must be specified when shapes of x and weights differ.")
elif isinstance(axis, tuple):
raise NotImplementedError("Weighted average over tuple axis not implemented yet.")
raise ValueError(
"Weighted average over tuple axis requires weights to be of the same shape as x."
)
if weights.ndim != 1:
raise TypeError("1D weights expected when shapes of x and weights differ.")
if weights.gshape[0] != x.gshape[axis]:
Expand Down
2 changes: 1 addition & 1 deletion heat/core/tests/test_statistics.py
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Expand Up @@ -306,7 +306,7 @@ def test_average(self):
ht.average(random_5d, weights=random_weights.numpy(), axis=axis)
with self.assertRaises(TypeError):
ht.average(random_5d, weights=random_weights, axis=None)
with self.assertRaises(NotImplementedError):
with self.assertRaises(ValueError):
ht.average(random_5d, weights=random_weights, axis=(1, 2))
random_weights = ht.random.randn(random_5d.gshape[axis], random_5d.gshape[axis + 1])
with self.assertRaises(TypeError):
Expand Down