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)))
