def test_range_error():
idx = pd.Index([0, 1, 1, 2, 3, 5, 8, 13])
dp = DeterministicProcess(
idx, constant=True, order=2, seasonal=True, period=2
)
with pytest.raises(TypeError, match="The index in the deterministic"):
dp.range(0, 12)
def test_determintic_term_equiv(index):
base = DeterministicProcess(pd.RangeIndex(0, 200), constant=True, order=2)
dp = DeterministicProcess(index, constant=True, order=2)
np.testing.assert_array_equal(base.in_sample(), dp.in_sample())
np.testing.assert_array_equal(base.out_of_sample(37), dp.out_of_sample(37))
np.testing.assert_array_equal(base.range(200, 237), dp.range(200, 237))
np.testing.assert_array_equal(base.range(50, 150), dp.range(50, 150))
np.testing.assert_array_equal(base.range(50, 250), dp.range(50, 250))
def test_range_casting():
idx = np.arange(120)
dp = DeterministicProcess(
idx, constant=True, order=1, seasonal=True, period=12
)
idx = pd.RangeIndex(0, 120)
dp2 = DeterministicProcess(
idx, constant=True, order=1, seasonal=True, period=12
)
pd.testing.assert_frame_equal(dp.in_sample(), dp2.in_sample())
pd.testing.assert_frame_equal(dp.range(100, 150), dp2.range(100, 150))
det_proc.out_of_sample(15)
# `range(start, stop)` can also be used to produce the deterministic terms
# over any range including in- and out-of-sample.
#
# ### Notes
#
# * When the index is a pandas `DatetimeIndex` or a `PeriodIndex`, then
# `start` and `stop` can be date-like (strings, e.g., "2020-06-01", or
# Timestamp) or integers.
# * `stop` is always included in the range. While this is not very
# Pythonic, it is needed since both statsmodels and Pandas include `stop`
# when working with date-like slices.
det_proc.range(190, 210)
# ## Using a Date-like Index
#
# Next, we show the same steps using a `PeriodIndex`.
index = pd.period_range("2020-03-01", freq="M", periods=60)
det_proc = DeterministicProcess(index, constant=True, fourier=2)
det_proc.in_sample().head(12)
det_proc.out_of_sample(12)
# `range` accepts date-like arguments, which are usually given as strings.
det_proc.range("2025-01", "2026-01")
def test_non_unit_range():
idx = pd.RangeIndex(0, 700, 7)
dp = DeterministicProcess(idx, constant=True)
with pytest.raises(ValueError, match="The step of the index is not 1"):
dp.range(11, 900)
def test_range_index_basic():
idx = pd.date_range("2000-1-1", freq="M", periods=120)
dp = DeterministicProcess(idx, constant=True, order=1, seasonal=True)
dp.range("2001-1-1", "2008-1-1")
dp.range("2001-1-1", "2015-1-1")
dp.range("2013-1-1", "2008-1-1")
dp.range(0, 100)
dp.range(100, 150)
dp.range(130, 150)
with pytest.raises(ValueError):
dp.range("1990-1-1", "2010-1-1")
idx = pd.period_range("2000-1-1", freq="M", periods=120)
dp = DeterministicProcess(idx, constant=True, order=1, seasonal=True)
dp.range("2001-1-1", "2008-1-1")
dp.range("2001-1-1", "2015-1-1")
dp.range("2013-1-1", "2008-1-1")
with pytest.raises(ValueError, match="start must be non-negative"):
dp.range(-7, 200)
dp.range(0, 100)
dp.range(100, 150)
dp.range(130, 150)
idx = pd.RangeIndex(0, 120)
dp = DeterministicProcess(idx,
constant=True,
order=1,
seasonal=True,
period=12)
dp.range(0, 100)
dp.range(100, 150)
dp.range(120, 150)
dp.range(130, 150)
with pytest.raises(ValueError):
dp.range(-10, 0)