projektAI/venv/Lib/site-packages/pandas/tests/arrays/test_numpy.py

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2021-06-06 22:13:05 +02:00
"""
Additional tests for PandasArray that aren't covered by
the interface tests.
"""
import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
from pandas.arrays import PandasArray
from pandas.core.arrays.numpy_ import PandasDtype
@pytest.fixture(
params=[
np.array(["a", "b"], dtype=object),
np.array([0, 1], dtype=float),
np.array([0, 1], dtype=int),
np.array([0, 1 + 2j], dtype=complex),
np.array([True, False], dtype=bool),
np.array([0, 1], dtype="datetime64[ns]"),
np.array([0, 1], dtype="timedelta64[ns]"),
]
)
def any_numpy_array(request):
"""
Parametrized fixture for NumPy arrays with different dtypes.
This excludes string and bytes.
"""
return request.param
# ----------------------------------------------------------------------------
# PandasDtype
@pytest.mark.parametrize(
"dtype, expected",
[
("bool", True),
("int", True),
("uint", True),
("float", True),
("complex", True),
("str", False),
("bytes", False),
("datetime64[ns]", False),
("object", False),
("void", False),
],
)
def test_is_numeric(dtype, expected):
dtype = PandasDtype(dtype)
assert dtype._is_numeric is expected
@pytest.mark.parametrize(
"dtype, expected",
[
("bool", True),
("int", False),
("uint", False),
("float", False),
("complex", False),
("str", False),
("bytes", False),
("datetime64[ns]", False),
("object", False),
("void", False),
],
)
def test_is_boolean(dtype, expected):
dtype = PandasDtype(dtype)
assert dtype._is_boolean is expected
def test_repr():
dtype = PandasDtype(np.dtype("int64"))
assert repr(dtype) == "PandasDtype('int64')"
def test_constructor_from_string():
result = PandasDtype.construct_from_string("int64")
expected = PandasDtype(np.dtype("int64"))
assert result == expected
# ----------------------------------------------------------------------------
# Construction
def test_constructor_no_coercion():
with pytest.raises(ValueError, match="NumPy array"):
PandasArray([1, 2, 3])
def test_series_constructor_with_copy():
ndarray = np.array([1, 2, 3])
ser = pd.Series(PandasArray(ndarray), copy=True)
assert ser.values is not ndarray
def test_series_constructor_with_astype():
ndarray = np.array([1, 2, 3])
result = pd.Series(PandasArray(ndarray), dtype="float64")
expected = pd.Series([1.0, 2.0, 3.0], dtype="float64")
tm.assert_series_equal(result, expected)
def test_from_sequence_dtype():
arr = np.array([1, 2, 3], dtype="int64")
result = PandasArray._from_sequence(arr, dtype="uint64")
expected = PandasArray(np.array([1, 2, 3], dtype="uint64"))
tm.assert_extension_array_equal(result, expected)
def test_constructor_copy():
arr = np.array([0, 1])
result = PandasArray(arr, copy=True)
assert np.shares_memory(result._ndarray, arr) is False
def test_constructor_with_data(any_numpy_array):
nparr = any_numpy_array
arr = PandasArray(nparr)
assert arr.dtype.numpy_dtype == nparr.dtype
# ----------------------------------------------------------------------------
# Conversion
def test_to_numpy():
arr = PandasArray(np.array([1, 2, 3]))
result = arr.to_numpy()
assert result is arr._ndarray
result = arr.to_numpy(copy=True)
assert result is not arr._ndarray
result = arr.to_numpy(dtype="f8")
expected = np.array([1, 2, 3], dtype="f8")
tm.assert_numpy_array_equal(result, expected)
# ----------------------------------------------------------------------------
# Setitem
def test_setitem_series():
ser = pd.Series([1, 2, 3])
ser.array[0] = 10
expected = pd.Series([10, 2, 3])
tm.assert_series_equal(ser, expected)
def test_setitem(any_numpy_array):
nparr = any_numpy_array
arr = PandasArray(nparr, copy=True)
arr[0] = arr[1]
nparr[0] = nparr[1]
tm.assert_numpy_array_equal(arr.to_numpy(), nparr)
# ----------------------------------------------------------------------------
# Reductions
def test_bad_reduce_raises():
arr = np.array([1, 2, 3], dtype="int64")
arr = PandasArray(arr)
msg = "cannot perform not_a_method with type int"
with pytest.raises(TypeError, match=msg):
arr._reduce(msg)
def test_validate_reduction_keyword_args():
arr = PandasArray(np.array([1, 2, 3]))
msg = "the 'keepdims' parameter is not supported .*all"
with pytest.raises(ValueError, match=msg):
arr.all(keepdims=True)
# ----------------------------------------------------------------------------
# Ops
def test_ufunc():
arr = PandasArray(np.array([-1.0, 0.0, 1.0]))
result = np.abs(arr)
expected = PandasArray(np.abs(arr._ndarray))
tm.assert_extension_array_equal(result, expected)
r1, r2 = np.divmod(arr, np.add(arr, 2))
e1, e2 = np.divmod(arr._ndarray, np.add(arr._ndarray, 2))
e1 = PandasArray(e1)
e2 = PandasArray(e2)
tm.assert_extension_array_equal(r1, e1)
tm.assert_extension_array_equal(r2, e2)
def test_basic_binop():
# Just a basic smoke test. The EA interface tests exercise this
# more thoroughly.
x = PandasArray(np.array([1, 2, 3]))
result = x + x
expected = PandasArray(np.array([2, 4, 6]))
tm.assert_extension_array_equal(result, expected)
@pytest.mark.parametrize("dtype", [None, object])
def test_setitem_object_typecode(dtype):
arr = PandasArray(np.array(["a", "b", "c"], dtype=dtype))
arr[0] = "t"
expected = PandasArray(np.array(["t", "b", "c"], dtype=dtype))
tm.assert_extension_array_equal(arr, expected)
def test_setitem_no_coercion():
# https://github.com/pandas-dev/pandas/issues/28150
arr = PandasArray(np.array([1, 2, 3]))
with pytest.raises(ValueError, match="int"):
arr[0] = "a"
# With a value that we do coerce, check that we coerce the value
# and not the underlying array.
arr[0] = 2.5
assert isinstance(arr[0], (int, np.integer)), type(arr[0])
def test_setitem_preserves_views():
# GH#28150, see also extension test of the same name
arr = PandasArray(np.array([1, 2, 3]))
view1 = arr.view()
view2 = arr[:]
view3 = np.asarray(arr)
arr[0] = 9
assert view1[0] == 9
assert view2[0] == 9
assert view3[0] == 9
arr[-1] = 2.5
view1[-1] = 5
assert arr[-1] == 5