CCR/.venv/lib/python3.12/site-packages/xarray/tests/test_utils.py

386 lines
12 KiB
Python

from __future__ import annotations
from collections.abc import Hashable
from types import EllipsisType
import numpy as np
import pandas as pd
import pytest
from xarray.core import duck_array_ops, utils
from xarray.core.utils import (
attempt_import,
either_dict_or_kwargs,
infix_dims,
iterate_nested,
)
from xarray.tests import assert_array_equal, requires_dask
class TestAlias:
def test(self):
def new_method():
pass
old_method = utils.alias(new_method, "old_method")
assert "deprecated" in old_method.__doc__
with pytest.warns(Warning, match="deprecated"):
old_method()
@pytest.mark.parametrize(
["a", "b", "expected"],
[
[np.array(["a"]), np.array(["b"]), np.array(["a", "b"])],
[np.array([1], dtype="int64"), np.array([2], dtype="int64"), pd.Index([1, 2])],
],
)
def test_maybe_coerce_to_str(a, b, expected):
index = pd.Index(a).append(pd.Index(b))
actual = utils.maybe_coerce_to_str(index, [a, b])
assert_array_equal(expected, actual)
assert expected.dtype == actual.dtype
def test_maybe_coerce_to_str_minimal_str_dtype():
a = np.array(["a", "a_long_string"])
index = pd.Index(["a"])
actual = utils.maybe_coerce_to_str(index, [a])
expected = np.array("a")
assert_array_equal(expected, actual)
assert expected.dtype == actual.dtype
class TestArrayEquiv:
def test_0d(self):
# verify our work around for pd.isnull not working for 0-dimensional
# object arrays
assert duck_array_ops.array_equiv(0, np.array(0, dtype=object))
assert duck_array_ops.array_equiv(np.nan, np.array(np.nan, dtype=object))
assert not duck_array_ops.array_equiv(0, np.array(1, dtype=object))
class TestDictionaries:
@pytest.fixture(autouse=True)
def setup(self):
self.x = {"a": "A", "b": "B"}
self.y = {"c": "C", "b": "B"}
self.z = {"a": "Z"}
def test_equivalent(self):
assert utils.equivalent(0, 0)
assert utils.equivalent(np.nan, np.nan)
assert utils.equivalent(0, np.array(0.0))
assert utils.equivalent([0], np.array([0]))
assert utils.equivalent(np.array([0]), [0])
assert utils.equivalent(np.arange(3), 1.0 * np.arange(3))
assert not utils.equivalent(0, np.zeros(3))
def test_safe(self):
# should not raise exception:
utils.update_safety_check(self.x, self.y)
def test_unsafe(self):
with pytest.raises(ValueError):
utils.update_safety_check(self.x, self.z)
def test_compat_dict_intersection(self):
assert {"b": "B"} == utils.compat_dict_intersection(self.x, self.y)
assert {} == utils.compat_dict_intersection(self.x, self.z)
def test_compat_dict_union(self):
assert {"a": "A", "b": "B", "c": "C"} == utils.compat_dict_union(self.x, self.y)
with pytest.raises(
ValueError,
match=r"unsafe to merge dictionaries without "
"overriding values; conflicting key",
):
utils.compat_dict_union(self.x, self.z)
def test_dict_equiv(self):
x = {}
x["a"] = 3
x["b"] = np.array([1, 2, 3])
y = {}
y["b"] = np.array([1.0, 2.0, 3.0])
y["a"] = 3
assert utils.dict_equiv(x, y) # two nparrays are equal
y["b"] = [1, 2, 3] # np.array not the same as a list
assert utils.dict_equiv(x, y) # nparray == list
x["b"] = [1.0, 2.0, 3.0]
assert utils.dict_equiv(x, y) # list vs. list
x["c"] = None
assert not utils.dict_equiv(x, y) # new key in x
x["c"] = np.nan
y["c"] = np.nan
assert utils.dict_equiv(x, y) # as intended, nan is nan
x["c"] = np.inf
y["c"] = np.inf
assert utils.dict_equiv(x, y) # inf == inf
y = dict(y)
assert utils.dict_equiv(x, y) # different dictionary types are fine
y["b"] = 3 * np.arange(3)
assert not utils.dict_equiv(x, y) # not equal when arrays differ
def test_frozen(self):
x = utils.Frozen(self.x)
with pytest.raises(TypeError):
x["foo"] = "bar"
with pytest.raises(TypeError):
del x["a"]
with pytest.raises(AttributeError):
x.update(self.y)
assert x.mapping == self.x
assert repr(x) in (
"Frozen({'a': 'A', 'b': 'B'})",
"Frozen({'b': 'B', 'a': 'A'})",
)
def test_filtered(self):
x = utils.FilteredMapping(keys={"a"}, mapping={"a": 1, "b": 2})
assert "a" in x
assert "b" not in x
assert x["a"] == 1
assert list(x) == ["a"]
assert len(x) == 1
assert repr(x) == "FilteredMapping(keys={'a'}, mapping={'a': 1, 'b': 2})"
assert dict(x) == {"a": 1}
def test_repr_object():
obj = utils.ReprObject("foo")
assert repr(obj) == "foo"
assert isinstance(obj, Hashable)
assert not isinstance(obj, str)
def test_repr_object_magic_methods():
o1 = utils.ReprObject("foo")
o2 = utils.ReprObject("foo")
o3 = utils.ReprObject("bar")
o4 = "foo"
assert o1 == o2
assert o1 != o3
assert o1 != o4
assert hash(o1) == hash(o2)
assert hash(o1) != hash(o3)
assert hash(o1) != hash(o4)
def test_is_remote_uri():
assert utils.is_remote_uri("http://example.com")
assert utils.is_remote_uri("https://example.com")
assert not utils.is_remote_uri(" http://example.com")
assert not utils.is_remote_uri("example.nc")
class Test_is_uniform_and_sorted:
def test_sorted_uniform(self):
assert utils.is_uniform_spaced(np.arange(5))
def test_sorted_not_uniform(self):
assert not utils.is_uniform_spaced([-2, 1, 89])
def test_not_sorted_uniform(self):
assert not utils.is_uniform_spaced([1, -1, 3])
def test_not_sorted_not_uniform(self):
assert not utils.is_uniform_spaced([4, 1, 89])
def test_two_numbers(self):
assert utils.is_uniform_spaced([0, 1.7])
def test_relative_tolerance(self):
assert utils.is_uniform_spaced([0, 0.97, 2], rtol=0.1)
class Test_hashable:
def test_hashable(self):
for v in [False, 1, (2,), (3, 4), "four"]:
assert utils.hashable(v)
for v in [[5, 6], ["seven", "8"], {9: "ten"}]:
assert not utils.hashable(v)
@requires_dask
def test_dask_array_is_scalar():
# regression test for GH1684
import dask.array as da
y = da.arange(8, chunks=4)
assert not utils.is_scalar(y)
def test_hidden_key_dict():
hidden_key = "_hidden_key"
data = {"a": 1, "b": 2, hidden_key: 3}
data_expected = {"a": 1, "b": 2}
hkd = utils.HiddenKeyDict(data, [hidden_key])
assert len(hkd) == 2
assert hidden_key not in hkd
for k, v in data_expected.items():
assert hkd[k] == v
with pytest.raises(KeyError):
hkd[hidden_key]
with pytest.raises(KeyError):
del hkd[hidden_key]
def test_either_dict_or_kwargs():
result = either_dict_or_kwargs(dict(a=1), None, "foo")
expected = dict(a=1)
assert result == expected
result = either_dict_or_kwargs(None, dict(a=1), "foo")
expected = dict(a=1)
assert result == expected
with pytest.raises(ValueError, match=r"foo"):
result = either_dict_or_kwargs(dict(a=1), dict(a=1), "foo")
@pytest.mark.parametrize(
["supplied", "all_", "expected"],
[
(list("abc"), list("abc"), list("abc")),
(["a", ..., "c"], list("abc"), list("abc")),
(["a", ...], list("abc"), list("abc")),
(["c", ...], list("abc"), list("cab")),
([..., "b"], list("abc"), list("acb")),
([...], list("abc"), list("abc")),
],
)
def test_infix_dims(supplied, all_, expected):
result = list(infix_dims(supplied, all_))
assert result == expected
@pytest.mark.parametrize(
["supplied", "all_"], [([..., ...], list("abc")), ([...], list("aac"))]
)
def test_infix_dims_errors(supplied, all_):
with pytest.raises(ValueError):
list(infix_dims(supplied, all_))
@pytest.mark.parametrize(
["dim", "expected"],
[
pytest.param("a", ("a",), id="str"),
pytest.param(["a", "b"], ("a", "b"), id="list_of_str"),
pytest.param(["a", 1], ("a", 1), id="list_mixed"),
pytest.param(["a", ...], ("a", ...), id="list_with_ellipsis"),
pytest.param(("a", "b"), ("a", "b"), id="tuple_of_str"),
pytest.param(["a", ("b", "c")], ("a", ("b", "c")), id="list_with_tuple"),
pytest.param((("b", "c"),), (("b", "c"),), id="tuple_of_tuple"),
pytest.param({"a", 1}, tuple({"a", 1}), id="non_sequence_collection"),
pytest.param((), (), id="empty_tuple"),
pytest.param(set(), (), id="empty_collection"),
pytest.param(None, None, id="None"),
pytest.param(..., ..., id="ellipsis"),
],
)
def test_parse_dims_as_tuple(dim, expected) -> None:
all_dims = ("a", "b", 1, ("b", "c")) # selection of different Hashables
actual = utils.parse_dims_as_tuple(dim, all_dims, replace_none=False)
assert actual == expected
def test_parse_dims_set() -> None:
all_dims = ("a", "b", 1, ("b", "c")) # selection of different Hashables
dim = {"a", 1}
actual = utils.parse_dims_as_tuple(dim, all_dims)
assert set(actual) == dim
@pytest.mark.parametrize(
"dim", [pytest.param(None, id="None"), pytest.param(..., id="ellipsis")]
)
def test_parse_dims_replace_none(dim: None | EllipsisType) -> None:
all_dims = ("a", "b", 1, ("b", "c")) # selection of different Hashables
actual = utils.parse_dims_as_tuple(dim, all_dims, replace_none=True)
assert actual == all_dims
@pytest.mark.parametrize(
"dim",
[
pytest.param("x", id="str_missing"),
pytest.param(["a", "x"], id="list_missing_one"),
pytest.param(["x", 2], id="list_missing_all"),
],
)
def test_parse_dims_raises(dim) -> None:
all_dims = ("a", "b", 1, ("b", "c")) # selection of different Hashables
with pytest.raises(ValueError, match="'x'"):
utils.parse_dims_as_tuple(dim, all_dims, check_exists=True)
@pytest.mark.parametrize(
["dim", "expected"],
[
pytest.param("a", ("a",), id="str"),
pytest.param(["a", "b"], ("a", "b"), id="list"),
pytest.param([...], ("a", "b", "c"), id="list_only_ellipsis"),
pytest.param(["a", ...], ("a", "b", "c"), id="list_with_ellipsis"),
pytest.param(["a", ..., "b"], ("a", "c", "b"), id="list_with_middle_ellipsis"),
],
)
def test_parse_ordered_dims(dim, expected) -> None:
all_dims = ("a", "b", "c")
actual = utils.parse_ordered_dims(dim, all_dims)
assert actual == expected
def test_parse_ordered_dims_raises() -> None:
all_dims = ("a", "b", "c")
with pytest.raises(ValueError, match="'x' do not exist"):
utils.parse_ordered_dims("x", all_dims, check_exists=True)
with pytest.raises(ValueError, match="repeated dims"):
utils.parse_ordered_dims(["a", ...], all_dims + ("a",))
with pytest.raises(ValueError, match="More than one ellipsis"):
utils.parse_ordered_dims(["a", ..., "b", ...], all_dims)
@pytest.mark.parametrize(
"nested_list, expected",
[
([], []),
([1], [1]),
([1, 2, 3], [1, 2, 3]),
([[1]], [1]),
([[1, 2], [3, 4]], [1, 2, 3, 4]),
([[[1, 2, 3], [4]], [5, 6]], [1, 2, 3, 4, 5, 6]),
],
)
def test_iterate_nested(nested_list, expected):
assert list(iterate_nested(nested_list)) == expected
def test_find_stack_level():
assert utils.find_stack_level() == 1
assert utils.find_stack_level(test_mode=True) == 2
def f():
return utils.find_stack_level(test_mode=True)
assert f() == 3
def test_attempt_import() -> None:
"""Test optional dependency handling."""
np = attempt_import("numpy")
assert np.__name__ == "numpy"
with pytest.raises(ImportError, match="The foo package is required"):
attempt_import(module="foo")
with pytest.raises(ImportError, match="The foo package is required"):
attempt_import(module="foo.bar")