Bug fixes for Dataset.reduce() and n-dimensional cumsum/cumprod #2156
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Fixes GH1470, "Dataset.mean drops coordinates"
Fixes a bug where non-scalar data-variables that did not include the
aggregated dimension were not properly reduced:
Previously::
>>> ds = Dataset({'x': ('a', [2, 2]), 'y': 2, 'z': ('b', [2])})
>>> ds.var('a')
<xarray.Dataset>
Dimensions: (b: 1)
Dimensions without coordinates: b
Data variables:
x float64 0.0
y float64 0.0
z (b) int64 2
Now::
>>> ds.var('a')
<xarray.Dataset>
Dimensions: (b: 1)
Dimensions without coordinates: b
Data variables:
x int64 0
y int64 0
z (b) int64 0
Finally, adds support for n-dimensional cumsum() and cumprod(), reducing
over all dimensions of an array. (This was necessary as part of the above fix.)
stickler-ci
reviewed
May 17, 2018
xarray/tests/test_duck_array_ops.py
Outdated
| def test_cumprod_2d(): | ||
| inputs = np.array([[1, 2], [3, 4]]) | ||
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| expected = np.array([[1, 2], [3, 2*3*4]]) |
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E226 missing whitespace around arithmetic operator
jhamman
approved these changes
May 18, 2018
xarray/core/dataset.py
Outdated
| keep_attrs=keep_attrs, | ||
| allow_lazy=allow_lazy, | ||
| **kwargs) | ||
| # drop other data_vars |
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This was intentional, but I don't think it actually adds much value.
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Fixes GH1470, "Dataset.mean drops coordinates"
Fixes a bug where non-scalar data-variables that did not include the
aggregated dimension were not properly reduced:
Finally, adds support for n-dimensional cumsum() and cumprod(), reducing
over all dimensions of an array. (This was necessary as part of the above fix.)
whats-new.rstfor all changes andapi.rstfor new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later)