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)