def testTransformationReversals(): testInfo = utl_Tst.create_test_data_correlated_returns(numDims=1, n=100) data = testInfo['data'][:,0] dt = testInfo['dt'] hndl_Srs_Original = EMF_TestSeries_Handle() hndl_Srs_Original.set_series_dates(dt) hndl_Srs_Original.set_series_values(data) # utl_Tst.plot_data_series(hndl_Srs_Original) # testTransformationReversal_None(data, dt) # testTransformationReversal_Past_Lvl(data, dt, hndl_Srs_Original) testTransformationReversal_Past_FoD(data, dt, hndl_Srs_Original) testTransformationReversal_Future_FoD(data, dt, hndl_Srs_Original)
def plot_values(self, hndl_Word): ''' Plot the raw data, predicted data, and smoothed data (For testing) ''' from util_Testing import plot_data_series from handle_TestSeries import EMF_TestSeries_Handle raw_key = raw_word_key(hndl_Word) prd_key = prd_word_key(hndl_Word) raw = EMF_TestSeries_Handle() (raw.dates, raw.values) = self.get_values_by_col(raw_key, filter_nulls=True) prd = EMF_TestSeries_Handle() (prd.dates, prd.values) = self.get_values_by_col(prd_key, filter_nulls=True) smooth = EMF_TestSeries_Handle() smooth.values = savitzky_golay(np.array(prd.values)) smooth.dates = prd.dates plot_data_series(raw, prd, smooth)
def testTransformationReversal_Future_FoD(data, dt, hndl_Srs_Original):
trnsKwargs={FIRST_ORDER_DIFF_TIME: 10}
hndl_Trns = EMF_Transformation_Handle('Futr_Change', trnsKwargs=trnsKwargs)
dt_trns = hndl_Trns.transform_time(dt)
data_trns = hndl_Trns.transform_data(data)
hndl_Srs_Trns = EMF_TestSeries_Handle()
hndl_Srs_Trns.set_series_dates(dt_trns)
hndl_Srs_Trns.set_series_values(data_trns)
# utl_Tst.plot_data_series(hndl_Srs_Original, hndl_Srs_Trns)
assert np.all(dt_trns == dt[:-10])
assert data_trns[0] == data[10] - data[00]
dt_rvrs = hndl_Trns.reverse_transform_time(dt_trns)
data_rvrs = hndl_Trns.reverse_transform_data(data[:-10], predictionDelta=data_trns)
hndl_Srs_Rvrs = EMF_TestSeries_Handle()
hndl_Srs_Rvrs.set_series_dates(dt_rvrs)
hndl_Srs_Rvrs.set_series_values(data_rvrs)
utl_Tst.plot_data_series(hndl_Srs_Original, hndl_Srs_Rvrs)
assert np.all(dt_rvrs == dt[10:])
def testTransformationReversal_Past_Lvl(data, dt, hndl_Srs_Original):
trnsKwargs={'PeriodDiff': 10}
hndl_Trns = EMF_Transformation_Handle('Past_Lvl', trnsKwargs=trnsKwargs)
dt_trns = hndl_Trns.transform_time(dt)
data_trns = hndl_Trns.transform_data(data)
hndl_Srs_Trns = EMF_TestSeries_Handle()
hndl_Srs_Trns.set_series_dates(dt_trns)
hndl_Srs_Trns.set_series_values(data_trns)
# utl_Tst.plot_data_series(hndl_Srs_Original, hndl_Srs_Trns)
assert np.all(dt_trns == dt[10:])
dt_rvrs = hndl_Trns.reverse_transform_time(dt_trns)
data_rvrs = hndl_Trns.reverse_transform_data(data_trns)
hndl_Srs_Rvrs = EMF_TestSeries_Handle()
hndl_Srs_Rvrs.set_series_dates(dt_rvrs)
hndl_Srs_Rvrs.set_series_values(data_rvrs)
utl_Tst.plot_data_series(hndl_Srs_Original, hndl_Srs_Rvrs)
assert np.all(dt_rvrs == dt[:-10])
assert np.all(data_rvrs == data[:-10])
def test_Current_Level_Cat_pattern(data, hndl_Time):
hndl_Srs = EMF_TestSeries_Handle()
hndl_Srs.values = data
hndl_Srs.dates = hndl_Time.get_dates()
trns_kwargs = {NUM_RANGES:10, FIRST_ORDER_DIFF_TIME:10}
hndl_Trns = EMF_Transformation_Handle('Futr_Lvl_Cat', trnsKwargs=trns_kwargs)
trns_data = hndl_Trns.transform_data(data)
hndl_Trns.transform_time(hndl_Time)
hndl_Srs_Trns = EMF_TestSeries_Handle()
hndl_Srs_Trns.values = trns_data
hndl_Srs_Trns.dates = hndl_Time.get_dates()
utl_Tst.plot_data_series(hndl_Srs, hndl_Srs_Trns)
raise NotImplementedError
