def preset_season_factor_test(self): """Initial Season Factors should be presetable""" hwm = HoltWintersMethod(seasonLength=4) factors = [0,1,2,3] hwm.set_parameter("seasonValues", factors) data = [[0, 362.0], [1,385.0], [2, 432.0], [3, 341.0], [4, 382.0], [5, 409.0], [6, 498.0], [7, 387.0], [8, 473.0], [9, 513.0], [10, 582.0], [11, 474.0]] tsSrc = TimeSeries.from_twodim_list(data) seasonValues = hwm.initSeasonFactors(tsSrc) assert seasonValues == factors, "Preset Season Factors are not returned by initSeasonFactors" hwm.set_parameter("seasonValues", factors[:2]) try: hwm.initSeasonFactors(tsSrc) except AssertionError: pass else: assert False, "If preset season factors and season length do not comply, initSeasonFactors should throw an AssertionError" # pragma: no cover
def season_factor_initialization_test(self): """ Test if seasonal correction factors are initialized correctly.""" hwm = HoltWintersMethod(seasonLength=4) data = [[0, 362.0], [1,385.0], [2, 432.0], [3, 341.0], [4, 382.0], [5, 409.0], [6, 498.0], [7, 387.0], [8, 473.0], [9, 513.0], [10, 582.0], [11, 474.0]] tsSrc = TimeSeries.from_twodim_list(data) seasonValues = hwm.initSeasonFactors(tsSrc) #correctness is not proven, but will be enough for regression testing assert seasonValues == [0.9302895649920525, 0.9980629019785198, 1.1551483413078523, 0.9164991917215755], "Season Values are not initialized correctly" # pragma: no cover
def preset_season_factor_test(self): """Initial Season Factors should be presetable""" hwm = HoltWintersMethod(seasonLength=4) factors = [0, 1, 2, 3] hwm.set_parameter("seasonValues", factors) data = [[0, 362.0], [1, 385.0], [2, 432.0], [3, 341.0], [4, 382.0], [5, 409.0], [6, 498.0], [7, 387.0], [8, 473.0], [9, 513.0], [10, 582.0], [11, 474.0]] tsSrc = TimeSeries.from_twodim_list(data) seasonValues = hwm.initSeasonFactors(tsSrc) assert seasonValues == factors, "Preset Season Factors are not returned by initSeasonFactors" hwm.set_parameter("seasonValues", factors[:2]) try: hwm.initSeasonFactors(tsSrc) except AssertionError: pass else: assert False, "If preset season factors and season length do not comply, initSeasonFactors should throw an AssertionError" # pragma: no cover
def season_factor_initialization_test(self): """ Test if seasonal correction factors are initialized correctly.""" hwm = HoltWintersMethod(seasonLength=4) data = [[0, 362.0], [1, 385.0], [2, 432.0], [3, 341.0], [4, 382.0], [5, 409.0], [6, 498.0], [7, 387.0], [8, 473.0], [9, 513.0], [10, 582.0], [11, 474.0]] tsSrc = TimeSeries.from_twodim_list(data) seasonValues = hwm.initSeasonFactors(tsSrc) #correctness is not proven, but will be enough for regression testing assert seasonValues == [ 0.9302895649920525, 0.9980629019785198, 1.1551483413078523, 0.9164991917215755 ], "Season Values are not initialized correctly" # pragma: no cover