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from datetime import datetime, timedelta
import numpy as np
from numpy.random import randn
import pytest
import pandas.util._test_decorators as td
from pandas.compat import is_platform_little_endian
from pandas import DataFrame, Series, bdate_range, notna
@pytest.fixture(params=[True, False])
def raw(request):
return request.param
@pytest.fixture(
params=[
"triang",
"blackman",
"hamming",
"bartlett",
"bohman",
"blackmanharris",
"nuttall",
"barthann",
]
)
def win_types(request):
return request.param
@pytest.fixture(params=["kaiser", "gaussian", "general_gaussian", "exponential"])
def win_types_special(request):
return request.param
@pytest.fixture(
params=["sum", "mean", "median", "max", "min", "var", "std", "kurt", "skew"]
)
def arithmetic_win_operators(request):
return request.param
@pytest.fixture(params=["right", "left", "both", "neither"])
def closed(request):
return request.param
@pytest.fixture(params=[True, False])
def center(request):
return request.param
@pytest.fixture(params=[None, 1])
def min_periods(request):
return request.param
@pytest.fixture(params=[True, False])
def parallel(request):
"""parallel keyword argument for numba.jit"""
return request.param
@pytest.fixture(params=[True, False])
def nogil(request):
"""nogil keyword argument for numba.jit"""
return request.param
@pytest.fixture(params=[True, False])
def nopython(request):
"""nopython keyword argument for numba.jit"""
return request.param
@pytest.fixture(
params=[pytest.param("numba", marks=td.skip_if_no("numba", "0.46.0")), "cython"]
)
def engine(request):
"""engine keyword argument for rolling.apply"""
return request.param
@pytest.fixture(
params=[
pytest.param(("numba", True), marks=[pytest.mark.xfail(condition=not is_platform_little_endian(), reason="Numba may crash on s390x", run=False, strict=False),td.skip_if_no("numba", "0.46.0")]),
("cython", True),
("cython", False),
]
)
def engine_and_raw(request):
"""engine and raw keyword arguments for rolling.apply"""
return request.param
# create the data only once as we are not setting it
def _create_consistency_data():
def create_series():
return [
Series(dtype=object),
Series([np.nan]),
Series([np.nan, np.nan]),
Series([3.0]),
Series([np.nan, 3.0]),
Series([3.0, np.nan]),
Series([1.0, 3.0]),
Series([2.0, 2.0]),
Series([3.0, 1.0]),
Series(
[5.0, 5.0, 5.0, 5.0, np.nan, np.nan, np.nan, 5.0, 5.0, np.nan, np.nan]
),
Series(
[
np.nan,
5.0,
5.0,
5.0,
np.nan,
np.nan,
np.nan,
5.0,
5.0,
np.nan,
np.nan,
]
),
Series(
[
np.nan,
np.nan,
5.0,
5.0,
np.nan,
np.nan,
np.nan,
5.0,
5.0,
np.nan,
np.nan,
]
),
Series(
[
np.nan,
3.0,
np.nan,
3.0,
4.0,
5.0,
6.0,
np.nan,
np.nan,
7.0,
12.0,
13.0,
14.0,
15.0,
]
),
Series(
[
np.nan,
5.0,
np.nan,
2.0,
4.0,
0.0,
9.0,
np.nan,
np.nan,
3.0,
12.0,
13.0,
14.0,
15.0,
]
),
Series(
[
2.0,
3.0,
np.nan,
3.0,
4.0,
5.0,
6.0,
np.nan,
np.nan,
7.0,
12.0,
13.0,
14.0,
15.0,
]
),
Series(
[
2.0,
5.0,
np.nan,
2.0,
4.0,
0.0,
9.0,
np.nan,
np.nan,
3.0,
12.0,
13.0,
14.0,
15.0,
]
),
Series(range(10)),
Series(range(20, 0, -2)),
]
def create_dataframes():
return [
DataFrame(),
DataFrame(columns=["a"]),
DataFrame(columns=["a", "a"]),
DataFrame(columns=["a", "b"]),
DataFrame(np.arange(10).reshape((5, 2))),
DataFrame(np.arange(25).reshape((5, 5))),
DataFrame(np.arange(25).reshape((5, 5)), columns=["a", "b", 99, "d", "d"]),
] + [DataFrame(s) for s in create_series()]
def is_constant(x):
values = x.values.ravel("K")
return len(set(values[notna(values)])) == 1
def no_nans(x):
return x.notna().all().all()
# data is a tuple(object, is_constant, no_nans)
data = create_series() + create_dataframes()
return [(x, is_constant(x), no_nans(x)) for x in data]
@pytest.fixture(params=_create_consistency_data())
def consistency_data(request):
"""Create consistency data"""
return request.param
def _create_arr():
"""Internal function to mock an array."""
arr = randn(100)
locs = np.arange(20, 40)
arr[locs] = np.NaN
return arr
def _create_rng():
"""Internal function to mock date range."""
rng = bdate_range(datetime(2009, 1, 1), periods=100)
return rng
def _create_series():
"""Internal function to mock Series."""
arr = _create_arr()
series = Series(arr.copy(), index=_create_rng())
return series
def _create_frame():
"""Internal function to mock DataFrame."""
rng = _create_rng()
return DataFrame(randn(100, 10), index=rng, columns=np.arange(10))
@pytest.fixture
def nan_locs():
"""Make a range as loc fixture."""
return np.arange(20, 40)
@pytest.fixture
def arr():
"""Make an array as fixture."""
return _create_arr()
@pytest.fixture
def frame():
"""Make mocked frame as fixture."""
return _create_frame()
@pytest.fixture
def series():
"""Make mocked series as fixture."""
return _create_series()
@pytest.fixture(params=[_create_series(), _create_frame()])
def which(request):
"""Turn parametrized which as fixture for series and frame"""
return request.param
@pytest.fixture(params=["1 day", timedelta(days=1)])
def halflife_with_times(request):
"""Halflife argument for EWM when times is specified."""
return request.param
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