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
