def test_add_lag1d_drop(self): data = self.random_data lagmat = tsatools.lagmat(data, 3, trim='Both') lag_data = tsatools.add_lag(data, lags=3, drop=True, insert=True) assert_equal(lagmat, lag_data) # no insert, should be the same lag_data = tsatools.add_lag(data, lags=3, drop=True, insert=False) assert_equal(lagmat, lag_data)
def test_add_lag_noinsertatend_ndarray(self): data = self.macro_df.values nddata = data.astype(float) lagmat = tsatools.lagmat(nddata[:, -1], 3, trim='Both') results = np.column_stack((nddata[3:, :], lagmat)) lag_data = tsatools.add_lag(nddata, 3, 3, insert=False) assert_equal(lag_data, results) # should be the same as insert also check negative col number lag_data2 = tsatools.add_lag(nddata, -1, 3, insert=True) assert_equal(lag_data2, results)
def test_add_lag_noinsert_atend(self): data = self.macro_df.values nddata = data.astype(float) lagmat = tsatools.lagmat(nddata[:, -1], 3, trim='Both') results = np.column_stack((nddata[3:, :], lagmat)) lag_data = tsatools.add_lag(data, self.cpi_loc, 3, insert=False) assert_equal(lag_data, results) # should be the same as insert lag_data2 = tsatools.add_lag(data, self.cpi_loc, 3, insert=True) assert_equal(lag_data2, results)
def test_add_lag1d(self): data = self.random_data lagmat = tsatools.lagmat(data, 3, trim='Both') results = np.column_stack((data[3:], lagmat)) lag_data = tsatools.add_lag(data, lags=3, insert=True) assert_equal(results, lag_data) # add index data = data[:, None] lagmat = tsatools.lagmat(data, 3, trim='Both') # test for lagmat too results = np.column_stack((data[3:], lagmat)) lag_data = tsatools.add_lag(data, lags=3, insert=True) assert_equal(results, lag_data)
def test_add_lag1d_struct(self): data = np.zeros(100, dtype=[('variable', float)]) nddata = self.random_data data['variable'] = nddata lagmat = tsatools.lagmat(nddata, 3, trim='Both', original='in') lag_data = tsatools.add_lag(data, 'variable', lags=3, insert=True) assert_equal(lagmat, lag_data.view((float, 4))) lag_data = tsatools.add_lag(data, 'variable', lags=3, insert=False) assert_equal(lagmat, lag_data.view((float, 4))) lag_data = tsatools.add_lag(data, lags=3, insert=True) assert_equal(lagmat, lag_data.view((float, 4)))
def test_add_lag_noinsert(self): data = self.macro_df.values nddata = data.astype(float) lagmat = tsatools.lagmat(nddata[:, 2], 3, trim='Both') results = np.column_stack((nddata[3:, :], lagmat)) lag_data = tsatools.add_lag(data, self.realgdp_loc, 3, insert=False) assert_equal(lag_data, results)
def test_add_lag_ndarray(self): data = self.macro_df.values nddata = data.astype(float) lagmat = tsatools.lagmat(nddata[:, 2], 3, trim='Both') results = np.column_stack((nddata[3:, :3], lagmat, nddata[3:, -1])) lag_data = tsatools.add_lag(nddata, 2, 3) assert_equal(lag_data, results)
def test_add_lag_1d_drop_struct(self): data = np.zeros(100, dtype=[('variable', float)]) nddata = self.random_data data['variable'] = nddata lagmat = tsatools.lagmat(nddata, 3, trim='Both') lag_data = tsatools.add_lag(data, lags=3, drop=True) assert_equal(lagmat, lag_data.view((float, 3)))