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cube.aggregated_by output bounds #4315

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merged 7 commits into from
Dec 8, 2021
Merged

cube.aggregated_by output bounds #4315

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0fc254d
calculate groupby indices up front
rcomer Sep 14, 2021
b33b670
reduce code repetition
rcomer Sep 14, 2021
9988311
use min/max for non-monotonic coords
rcomer Sep 14, 2021
260982d
update failing tests; add and pass test for bounded case
rcomer Sep 14, 2021
fd361f8
whatsnew
rcomer Sep 14, 2021
75c4cb8
clarity tweaks
rcomer Sep 15, 2021
6ec1418
Merge branch 'main' into aggregated_by-bounds
lbdreyer Dec 8, 2021
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4 changes: 4 additions & 0 deletions docs/src/whatsnew/latest.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -136,6 +136,10 @@ This document explains the changes made to Iris for this release
array laziness, allowing efficient comparisons even with larger-than-memory
objects. (:pull:`4439`)

#. `@rcomer`_ modified :meth:`~iris.cube.Cube.aggregated_by` to calculate new
coordinate bounds using minimum and maximum for unordered coordinates,
fixing :issue:`1528`. (:pull:`4315`)


💣 Incompatible Changes
=======================
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83 changes: 44 additions & 39 deletions lib/iris/analysis/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2170,15 +2170,20 @@ def _compute_groupby_coords(self):
def _compute_shared_coords(self):
"""Create the new shared coordinates given the group slices."""

groupby_indices = []
groupby_bounds = []

# Iterate over the ordered dictionary in order to construct
# a list of tuple group boundary indexes.
# Iterate over the ordered dictionary in order to construct a list of
# tuple group indices, and a list of the respective bounds of those
# indices.
for key_slice in self._slices_by_key.values():
if isinstance(key_slice, tuple):
groupby_bounds.append((key_slice[0], key_slice[-1]))
indices = key_slice
else:
groupby_bounds.append((key_slice.start, key_slice.stop - 1))
indices = tuple(range(*key_slice.indices(self._stop)))

groupby_indices.append(indices)
groupby_bounds.append((indices[0], indices[-1]))

# Create new shared bounded coordinates.
for coord, dim in self._shared_coords:
Expand All @@ -2197,15 +2202,9 @@ def _compute_shared_coords(self):
new_shape += shape[:-1]
work_arr = work_arr.reshape(work_shape)

for key_slice in self._slices_by_key.values():
if isinstance(key_slice, slice):
indices = key_slice.indices(
coord.points.shape[dim]
)
key_slice = range(*indices)

for indices in groupby_indices:
for arr in work_arr:
new_points.append("|".join(arr.take(key_slice)))
new_points.append("|".join(arr.take(indices)))

# Reinstate flattened dimensions. Aggregated dim now leads.
new_points = np.array(new_points).reshape(new_shape)
Expand All @@ -2220,48 +2219,54 @@ def _compute_shared_coords(self):
raise ValueError(msg)
else:
new_bounds = []
if coord.has_bounds():
# Derive new coord's bounds from bounds.
item = coord.bounds
maxmin_axis = (dim, -1)
first_choices = coord.bounds.take(0, -1)
last_choices = coord.bounds.take(1, -1)
else:
# Derive new coord's bounds from points.
item = coord.points
maxmin_axis = dim
first_choices = last_choices = coord.points

# Check whether item is monotonic along the dimension of interest.
deltas = np.diff(item, 1, dim)
monotonic = np.all(deltas >= 0) or np.all(deltas <= 0)

# Construct list of coordinate group boundary pairs.
for start, stop in groupby_bounds:
if coord.has_bounds():
# Collapse group bounds into bounds.
if monotonic:
# Use first and last bound or point for new bounds.
for start, stop in groupby_bounds:
if (
getattr(coord, "circular", False)
and (stop + 1) == coord.shape[dim]
and (stop + 1) == self._stop
):
new_bounds.append(
[
coord.bounds.take(start, dim).take(0, -1),
coord.bounds.take(0, dim).take(0, -1)
+ coord.units.modulus,
]
)
else:
new_bounds.append(
[
coord.bounds.take(start, dim).take(0, -1),
coord.bounds.take(stop, dim).take(1, -1),
]
)
else:
# Collapse group points into bounds.
if getattr(coord, "circular", False) and (
stop + 1
) == len(coord.points):
new_bounds.append(
[
coord.points.take(start, dim),
coord.points.take(0, dim)
first_choices.take(start, dim),
first_choices.take(0, dim)
+ coord.units.modulus,
]
)
else:
new_bounds.append(
[
coord.points.take(start, dim),
coord.points.take(stop, dim),
first_choices.take(start, dim),
last_choices.take(stop, dim),
]
)
else:
# Use min and max bound or point for new bounds.
for indices in groupby_indices:
item_slice = item.take(indices, dim)
new_bounds.append(
[
item_slice.min(axis=maxmin_axis),
item_slice.max(axis=maxmin_axis),
]
)

# Bounds needs to be an array with the length 2 start-stop
# dimension last, and the aggregated dimension back in its
Expand Down
26 changes: 24 additions & 2 deletions lib/iris/tests/unit/cube/test_Cube.py
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Original file line number Diff line number Diff line change
Expand Up @@ -757,7 +757,29 @@ def test_agg_by_label(self):
res_cube = self.cube.aggregated_by("label", self.mock_agg)
val_coord = AuxCoord(
np.array([1.0, 0.5, 1.0]),
bounds=np.array([[0, 2], [0, 1], [2, 0]]),
bounds=np.array([[0, 2], [0, 1], [0, 2]]),
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long_name="val",
)
label_coord = AuxCoord(
np.array(["alpha", "beta", "gamma"]),
long_name="label",
units="no_unit",
)
self.assertEqual(res_cube.coord("val"), val_coord)
self.assertEqual(res_cube.coord("label"), label_coord)

def test_agg_by_label_bounded(self):
# Aggregate a cube on a string coordinate label where label
# and val entries are not in step; the resulting cube has a val
# coord of bounded cells and a label coord of single string entries.
val_points = self.cube.coord("val").points
self.cube.coord("val").bounds = np.array(
[val_points - 0.5, val_points + 0.5]
).T
res_cube = self.cube.aggregated_by("label", self.mock_agg)
val_coord = AuxCoord(
np.array([1.0, 0.5, 1.0]),
bounds=np.array([[-0.5, 2.5], [-0.5, 1.5], [-0.5, 2.5]]),
long_name="val",
)
label_coord = AuxCoord(
Expand Down Expand Up @@ -890,7 +912,7 @@ def test_agg_by_label__lazy(self):
res_cube = self.cube.aggregated_by("label", MEAN)
val_coord = AuxCoord(
np.array([1.0, 0.5, 1.0]),
bounds=np.array([[0, 2], [0, 1], [2, 0]]),
bounds=np.array([[0, 2], [0, 1], [0, 2]]),
long_name="val",
)
label_coord = AuxCoord(
Expand Down