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import numpy as np
import pytest
import xarray as xr
from xarray.core import dtypes, merge
from xarray.core.merge import MergeError
from xarray.testing import assert_identical
from . import raises_regex
from .test_dataset import create_test_data
class TestMergeInternals:
def test_broadcast_dimension_size(self):
actual = merge.broadcast_dimension_size(
[xr.Variable("x", [1]), xr.Variable("y", [2, 1])]
)
assert actual == {"x": 1, "y": 2}
actual = merge.broadcast_dimension_size(
[xr.Variable(("x", "y"), [[1, 2]]), xr.Variable("y", [2, 1])]
)
assert actual == {"x": 1, "y": 2}
with pytest.raises(ValueError):
merge.broadcast_dimension_size(
[xr.Variable(("x", "y"), [[1, 2]]), xr.Variable("y", [2])]
)
class TestMergeFunction:
def test_merge_arrays(self):
data = create_test_data()
actual = xr.merge([data.var1, data.var2])
expected = data[["var1", "var2"]]
assert actual.identical(expected)
def test_merge_datasets(self):
data = create_test_data()
actual = xr.merge([data[["var1"]], data[["var2"]]])
expected = data[["var1", "var2"]]
assert actual.identical(expected)
actual = xr.merge([data, data])
assert actual.identical(data)
def test_merge_dataarray_unnamed(self):
data = xr.DataArray([1, 2], dims="x")
with raises_regex(ValueError, "without providing an explicit name"):
xr.merge([data])
def test_merge_arrays_attrs_default(self):
var1_attrs = {"a": 1, "b": 2}
var2_attrs = {"a": 1, "c": 3}
expected_attrs = {}
data = create_test_data()
data.var1.attrs = var1_attrs
data.var2.attrs = var2_attrs
actual = xr.merge([data.var1, data.var2])
expected = data[["var1", "var2"]]
expected.attrs = expected_attrs
assert actual.identical(expected)
@pytest.mark.parametrize(
"combine_attrs, var1_attrs, var2_attrs, expected_attrs, expect_exception",
[
(
"no_conflicts",
{"a": 1, "b": 2},
{"a": 1, "c": 3},
{"a": 1, "b": 2, "c": 3},
False,
),
("no_conflicts", {"a": 1, "b": 2}, {}, {"a": 1, "b": 2}, False),
("no_conflicts", {}, {"a": 1, "c": 3}, {"a": 1, "c": 3}, False),
(
"no_conflicts",
{"a": 1, "b": 2},
{"a": 4, "c": 3},
{"a": 1, "b": 2, "c": 3},
True,
),
("drop", {"a": 1, "b": 2}, {"a": 1, "c": 3}, {}, False),
("identical", {"a": 1, "b": 2}, {"a": 1, "b": 2}, {"a": 1, "b": 2}, False),
("identical", {"a": 1, "b": 2}, {"a": 1, "c": 3}, {"a": 1, "b": 2}, True),
(
"override",
{"a": 1, "b": 2},
{"a": 4, "b": 5, "c": 3},
{"a": 1, "b": 2},
False,
),
],
)
def test_merge_arrays_attrs(
self, combine_attrs, var1_attrs, var2_attrs, expected_attrs, expect_exception
):
data = create_test_data()
data.var1.attrs = var1_attrs
data.var2.attrs = var2_attrs
if expect_exception:
with raises_regex(MergeError, "combine_attrs"):
actual = xr.merge([data.var1, data.var2], combine_attrs=combine_attrs)
else:
actual = xr.merge([data.var1, data.var2], combine_attrs=combine_attrs)
expected = data[["var1", "var2"]]
expected.attrs = expected_attrs
assert actual.identical(expected)
def test_merge_dicts_simple(self):
actual = xr.merge([{"foo": 0}, {"bar": "one"}, {"baz": 3.5}])
expected = xr.Dataset({"foo": 0, "bar": "one", "baz": 3.5})
assert actual.identical(expected)
def test_merge_dicts_dims(self):
actual = xr.merge([{"y": ("x", [13])}, {"x": [12]}])
expected = xr.Dataset({"x": [12], "y": ("x", [13])})
assert actual.identical(expected)
def test_merge_error(self):
ds = xr.Dataset({"x": 0})
with pytest.raises(xr.MergeError):
xr.merge([ds, ds + 1])
def test_merge_alignment_error(self):
ds = xr.Dataset(coords={"x": [1, 2]})
other = xr.Dataset(coords={"x": [2, 3]})
with raises_regex(ValueError, "indexes .* not equal"):
xr.merge([ds, other], join="exact")
def test_merge_wrong_input_error(self):
with raises_regex(TypeError, "objects must be an iterable"):
xr.merge([1])
ds = xr.Dataset(coords={"x": [1, 2]})
with raises_regex(TypeError, "objects must be an iterable"):
xr.merge({"a": ds})
with raises_regex(TypeError, "objects must be an iterable"):
xr.merge([ds, 1])
def test_merge_no_conflicts_single_var(self):
ds1 = xr.Dataset({"a": ("x", [1, 2]), "x": [0, 1]})
ds2 = xr.Dataset({"a": ("x", [2, 3]), "x": [1, 2]})
expected = xr.Dataset({"a": ("x", [1, 2, 3]), "x": [0, 1, 2]})
assert expected.identical(xr.merge([ds1, ds2], compat="no_conflicts"))
assert expected.identical(xr.merge([ds2, ds1], compat="no_conflicts"))
assert ds1.identical(xr.merge([ds1, ds2], compat="no_conflicts", join="left"))
assert ds2.identical(xr.merge([ds1, ds2], compat="no_conflicts", join="right"))
expected = xr.Dataset({"a": ("x", [2]), "x": [1]})
assert expected.identical(
xr.merge([ds1, ds2], compat="no_conflicts", join="inner")
)
with pytest.raises(xr.MergeError):
ds3 = xr.Dataset({"a": ("x", [99, 3]), "x": [1, 2]})
xr.merge([ds1, ds3], compat="no_conflicts")
with pytest.raises(xr.MergeError):
ds3 = xr.Dataset({"a": ("y", [2, 3]), "y": [1, 2]})
xr.merge([ds1, ds3], compat="no_conflicts")
def test_merge_no_conflicts_multi_var(self):
data = create_test_data()
data1 = data.copy(deep=True)
data2 = data.copy(deep=True)
expected = data[["var1", "var2"]]
actual = xr.merge([data1.var1, data2.var2], compat="no_conflicts")
assert expected.identical(actual)
data1["var1"][:, :5] = np.nan
data2["var1"][:, 5:] = np.nan
data1["var2"][:4, :] = np.nan
data2["var2"][4:, :] = np.nan
del data2["var3"]
actual = xr.merge([data1, data2], compat="no_conflicts")
assert data.equals(actual)
def test_merge_no_conflicts_preserve_attrs(self):
data = xr.Dataset({"x": ([], 0, {"foo": "bar"})})
actual = xr.merge([data, data])
assert data.identical(actual)
def test_merge_no_conflicts_broadcast(self):
datasets = [xr.Dataset({"x": ("y", [0])}), xr.Dataset({"x": np.nan})]
actual = xr.merge(datasets)
expected = xr.Dataset({"x": ("y", [0])})
assert expected.identical(actual)
datasets = [xr.Dataset({"x": ("y", [np.nan])}), xr.Dataset({"x": 0})]
actual = xr.merge(datasets)
assert expected.identical(actual)
class TestMergeMethod:
def test_merge(self):
data = create_test_data()
ds1 = data[["var1"]]
ds2 = data[["var3"]]
expected = data[["var1", "var3"]]
actual = ds1.merge(ds2)
assert expected.identical(actual)
actual = ds2.merge(ds1)
assert expected.identical(actual)
actual = data.merge(data)
assert data.identical(actual)
actual = data.reset_coords(drop=True).merge(data)
assert data.identical(actual)
actual = data.merge(data.reset_coords(drop=True))
assert data.identical(actual)
with pytest.raises(ValueError):
ds1.merge(ds2.rename({"var3": "var1"}))
with raises_regex(ValueError, "should be coordinates or not"):
data.reset_coords().merge(data)
with raises_regex(ValueError, "should be coordinates or not"):
data.merge(data.reset_coords())
def test_merge_broadcast_equals(self):
ds1 = xr.Dataset({"x": 0})
ds2 = xr.Dataset({"x": ("y", [0, 0])})
actual = ds1.merge(ds2)
assert ds2.identical(actual)
actual = ds2.merge(ds1)
assert ds2.identical(actual)
actual = ds1.copy()
actual.update(ds2)
assert ds2.identical(actual)
ds1 = xr.Dataset({"x": np.nan})
ds2 = xr.Dataset({"x": ("y", [np.nan, np.nan])})
actual = ds1.merge(ds2)
assert ds2.identical(actual)
def test_merge_compat(self):
ds1 = xr.Dataset({"x": 0})
ds2 = xr.Dataset({"x": 1})
for compat in ["broadcast_equals", "equals", "identical", "no_conflicts"]:
with pytest.raises(xr.MergeError):
ds1.merge(ds2, compat=compat)
ds2 = xr.Dataset({"x": [0, 0]})
for compat in ["equals", "identical"]:
with raises_regex(ValueError, "should be coordinates or not"):
ds1.merge(ds2, compat=compat)
ds2 = xr.Dataset({"x": ((), 0, {"foo": "bar"})})
with pytest.raises(xr.MergeError):
ds1.merge(ds2, compat="identical")
with raises_regex(ValueError, "compat=.* invalid"):
ds1.merge(ds2, compat="foobar")
assert ds1.identical(ds1.merge(ds2, compat="override"))
def test_merge_auto_align(self):
ds1 = xr.Dataset({"a": ("x", [1, 2]), "x": [0, 1]})
ds2 = xr.Dataset({"b": ("x", [3, 4]), "x": [1, 2]})
expected = xr.Dataset(
{"a": ("x", [1, 2, np.nan]), "b": ("x", [np.nan, 3, 4])}, {"x": [0, 1, 2]}
)
assert expected.identical(ds1.merge(ds2))
assert expected.identical(ds2.merge(ds1))
expected = expected.isel(x=slice(2))
assert expected.identical(ds1.merge(ds2, join="left"))
assert expected.identical(ds2.merge(ds1, join="right"))
expected = expected.isel(x=slice(1, 2))
assert expected.identical(ds1.merge(ds2, join="inner"))
assert expected.identical(ds2.merge(ds1, join="inner"))
@pytest.mark.parametrize("fill_value", [dtypes.NA, 2, 2.0, {"a": 2, "b": 1}])
def test_merge_fill_value(self, fill_value):
ds1 = xr.Dataset({"a": ("x", [1, 2]), "x": [0, 1]})
ds2 = xr.Dataset({"b": ("x", [3, 4]), "x": [1, 2]})
if fill_value == dtypes.NA:
# if we supply the default, we expect the missing value for a
# float array
fill_value_a = fill_value_b = np.nan
elif isinstance(fill_value, dict):
fill_value_a = fill_value["a"]
fill_value_b = fill_value["b"]
else:
fill_value_a = fill_value_b = fill_value
expected = xr.Dataset(
{"a": ("x", [1, 2, fill_value_a]), "b": ("x", [fill_value_b, 3, 4])},
{"x": [0, 1, 2]},
)
assert expected.identical(ds1.merge(ds2, fill_value=fill_value))
assert expected.identical(ds2.merge(ds1, fill_value=fill_value))
assert expected.identical(xr.merge([ds1, ds2], fill_value=fill_value))
def test_merge_no_conflicts(self):
ds1 = xr.Dataset({"a": ("x", [1, 2]), "x": [0, 1]})
ds2 = xr.Dataset({"a": ("x", [2, 3]), "x": [1, 2]})
expected = xr.Dataset({"a": ("x", [1, 2, 3]), "x": [0, 1, 2]})
assert expected.identical(ds1.merge(ds2, compat="no_conflicts"))
assert expected.identical(ds2.merge(ds1, compat="no_conflicts"))
assert ds1.identical(ds1.merge(ds2, compat="no_conflicts", join="left"))
assert ds2.identical(ds1.merge(ds2, compat="no_conflicts", join="right"))
expected2 = xr.Dataset({"a": ("x", [2]), "x": [1]})
assert expected2.identical(ds1.merge(ds2, compat="no_conflicts", join="inner"))
with pytest.raises(xr.MergeError):
ds3 = xr.Dataset({"a": ("x", [99, 3]), "x": [1, 2]})
ds1.merge(ds3, compat="no_conflicts")
with pytest.raises(xr.MergeError):
ds3 = xr.Dataset({"a": ("y", [2, 3]), "y": [1, 2]})
ds1.merge(ds3, compat="no_conflicts")
def test_merge_dataarray(self):
ds = xr.Dataset({"a": 0})
da = xr.DataArray(data=1, name="b")
assert_identical(ds.merge(da), xr.merge([ds, da]))
|
