def test_acf():
# upstream this is in tsa.tests.test_tsa_tools
acf_x = acf(x100, unbiased=False, fft=False)[0][:21]
assert_array_almost_equal(mlacf.acf100.ravel(), acf_x, 8)
# TODO: why only dec=8?
acf_x = acf(x1000, unbiased=False, fft=False)[0][:21]
assert_array_almost_equal(mlacf.acf1000.ravel(), acf_x, 8)
def test_raise(self):
with pytest.raises(MissingDataError):
acf(self.x,
nlags=40,
qstat=True,
alpha=0.5,
missing='raise',
fft=False)
def setup_class(cls):
cls.x = np.concatenate((np.array([np.nan]), cls.x))
cls.acf = cls.results['acvar'] # drop and conservative
cls.qstat = cls.results['Q1']
cls.res_drop = acf(cls.x,
nlags=40,
qstat=True,
alpha=.05,
missing='drop',
fft=False)
cls.res_conservative = acf(cls.x,
nlags=40,
qstat=True,
alpha=.05,
missing='conservative',
fft=False)
cls.acf_none = np.empty(40) * np.nan # lags 1 to 40 inclusive
cls.qstat_none = np.empty(40) * np.nan
cls.res_none = acf(cls.x,
nlags=40,
qstat=True,
alpha=.05,
missing='none',
fft=False)
def setup_class(cls):
cls.acf = cls.results['acvar']
cls.qstat = cls.results['Q1']
cls.res1 = acf(cls.x, nlags=40, qstat=True, alpha=.05, fft=False)
cls.confint_res = cls.results[['acvar_lb', 'acvar_ub']].values
def test_acf_warns(acovf_data):
# GH#4937
with pytest.warns(FutureWarning):
acf(acovf_data, nlags=40)
def test_acf_fft_dataframe():
# GH#322
data = sunspots.load_pandas().data[['SUNACTIVITY']]
result = acf(data, fft=True)[0]
assert result.ndim == 1
def setup_class(cls):
cls.acf = cls.results['acvarfft']
cls.qstat = cls.results['Q1']
cls.res1 = acf(cls.x, nlags=40, qstat=True, fft=True)