def index(date_type):
dates = [
date_type(1, 1, 1),
date_type(1, 2, 1),
date_type(2, 1, 1),
date_type(2, 2, 1)
]
return CFTimeIndex(dates)
def test_cftimeindex_shift(index, freq):
date_type = index.date_type
expected_dates = [date_type(1, 1, 3), date_type(1, 2, 3),
date_type(2, 1, 3), date_type(2, 2, 3)]
expected = CFTimeIndex(expected_dates)
result = index.shift(2, freq)
assert result.equals(expected)
assert isinstance(result, CFTimeIndex)
def index_with_name(date_type):
dates = [
date_type(1, 1, 1),
date_type(1, 2, 1),
date_type(2, 1, 1),
date_type(2, 2, 1)
]
return CFTimeIndex(dates, name='foo')
def monotonic_decreasing_index(date_type):
dates = [
date_type(2, 2, 1),
date_type(2, 1, 1),
date_type(1, 2, 1),
date_type(1, 1, 1)
]
return CFTimeIndex(dates)
def test_cftimeindex_radd(index):
date_type = index.date_type
expected_dates = [date_type(1, 1, 2), date_type(1, 2, 2),
date_type(2, 1, 2), date_type(2, 2, 2)]
expected = CFTimeIndex(expected_dates)
result = timedelta(days=1) + index
assert result.equals(expected)
assert isinstance(result, CFTimeIndex)
def test_time_bnds(freq, datetime_index, cftime_index):
da_datetime = da(datetime_index).resample(time=freq)
da_cftime = da(cftime_index).resample(time=freq)
cftime_bounds = time_bnds(da_cftime, freq=freq)
cftime_starts, cftime_ends = zip(*cftime_bounds)
cftime_starts = CFTimeIndex(cftime_starts).to_datetimeindex()
cftime_ends = CFTimeIndex(cftime_ends).to_datetimeindex()
# cftime resolution goes down to microsecond only, code below corrects
# that to allow for comparison with pandas datetime
cftime_ends += np.timedelta64(999, "ns")
datetime_starts = da_datetime._full_index.to_period(freq).start_time
datetime_ends = da_datetime._full_index.to_period(freq).end_time
assert_array_equal(cftime_starts, datetime_starts)
assert_array_equal(cftime_ends, datetime_ends)
def test_safe_cast_to_index_cftimeindex():
date_types = _all_cftime_date_types()
for date_type in date_types.values():
dates = [date_type(1, 1, day) for day in range(1, 20)]
expected = CFTimeIndex(dates)
actual = utils.safe_cast_to_index(np.array(dates))
assert_array_equal(expected, actual)
assert expected.dtype == actual.dtype
assert isinstance(actual, type(expected))
def test_cftimeindex_sub_timedelta_array(index, other):
date_type = index.date_type
expected_dates = [
date_type(1, 1, 2),
date_type(1, 2, 2),
date_type(2, 1, 2),
date_type(2, 2, 2),
]
expected = CFTimeIndex(expected_dates)
result = index + timedelta(days=2)
result = result - other
assert result.equals(expected)
assert isinstance(result, CFTimeIndex)
def test_safe_cast_to_index_cftimeindex(enable_cftimeindex):
date_types = _all_cftime_date_types()
for date_type in date_types.values():
dates = [date_type(1, 1, day) for day in range(1, 20)]
if enable_cftimeindex and has_cftime:
expected = CFTimeIndex(dates)
else:
expected = pd.Index(dates)
with set_options(enable_cftimeindex=enable_cftimeindex):
actual = utils.safe_cast_to_index(np.array(dates))
assert_array_equal(expected, actual)
assert expected.dtype == actual.dtype
assert isinstance(actual, type(expected))
def cfindex_end_time(cfindex, freq):
"""
Get the end of a period for a pseudo-period index.
As we are using datetime indices to stand in for period indices, assumptions regarding the
period are made based on the given freq. IMPORTANT NOTE: this function cannot be used on greater-than-day
freq that start at the beginning of a month, e.g. 'MS', 'QS', 'AS' -- this mirrors pandas behavior.
Parameters
----------
cfindex : CFTimeIndex
CFTimeIndex as a proxy representation for CFPeriodIndex
freq : str
String specifying the frequency/offset such as 'MS', '2D', 'H', or '3T'
Returns
-------
CFTimeIndex
The ending datetimes of periods inferred from dates and freq
"""
return CFTimeIndex([cftime_end_time(date, freq) for date in cfindex])
def test_empty_cftimeindex():
index = CFTimeIndex([])
assert index.date_type is None
def test_constructor_with_name(index_with_name, name, expected_name):
result = CFTimeIndex(index_with_name, name=name).name
assert result == expected_name
def length_one_index(date_type):
dates = [date_type(1, 1, 1)]
return CFTimeIndex(dates)
"periods,expected",
[
(
2,
"""\
CFTimeIndex([2000-01-01 00:00:00, 2000-01-02 00:00:00],
dtype='object', length=2, calendar='gregorian', freq=None)""",
),
(
4,
"""\
CFTimeIndex([2000-01-01 00:00:00, 2000-01-02 00:00:00, 2000-01-03 00:00:00,
2000-01-04 00:00:00],
dtype='object', length=4, calendar='gregorian', freq='D')""",
),
(
101,
"""\
CFTimeIndex([2000-01-01 00:00:00, 2000-01-02 00:00:00, 2000-01-03 00:00:00,
2000-01-04 00:00:00, 2000-01-05 00:00:00, 2000-01-06 00:00:00,
2000-01-07 00:00:00, 2000-01-08 00:00:00, 2000-01-09 00:00:00,
2000-01-10 00:00:00,
...
2000-04-01 00:00:00, 2000-04-02 00:00:00, 2000-04-03 00:00:00,
2000-04-04 00:00:00, 2000-04-05 00:00:00, 2000-04-06 00:00:00,
2000-04-07 00:00:00, 2000-04-08 00:00:00, 2000-04-09 00:00:00,
2000-04-10 00:00:00],
dtype='object', length=101, calendar='gregorian', freq='D')""",
),
],
)
