def setUp(self):
self.season_period = 2
self.values = [np.array([[i+1], [i]]) for i in
range(1, self.season_period * 2+1)]
self.dataframe = DataFrame.from_items([('values', self.values)])
self.hwi = HoltWintersI(self.dataframe,
season_period=self.season_period)
self.hwi._init_starting_arrays()
self.coefs = [0.5] * 12
self.A, self.B, self.G = flats_to_matrix(self.coefs)
def setUp(self):
self.periods = 2
self.values = [
np.array([[i + 1], [i]]) for i in range(1, self.periods + 1)
]
self.dataframe = DataFrame.from_items([('values', self.values)])
self.model = HoltI(self.dataframe)
self.coefs = [0.5] * 8
self.A, self.B = flats_to_matrix(self.coefs)
self.model._init_starting_arrays()
def _check_initial_coefs(self, coefs):
"""Set up initial coefficients
:param coefs: list of coefs matrix [alpha, beta]
:raises ValueError: if given coefs negative or greater that 1
"""
alpha, beta = flats_to_matrix(coefs)
if any([
alpha is not None and not isinstance(alpha, np.matrix),
beta is not None and not isinstance(beta, np.matrix)
]):
raise ValueError(u"Given coef matrix should be instance of "
u"np.matrix")
if any([
not self._is_correct_coefs_matrix(alpha),
not self._is_correct_coefs_matrix(alpha)
]):
raise ValueError(u"All given matrix coefs values should be in "
u"range [0;1]")
def _extract_coefs(self, coefs):
"""Overriden coefs retreive function found by optimization algorithm"""
self.alpha, self.beta, self.gamma = self._coefs = flats_to_matrix(
coefs)
def _extract_coefs(self, coefs):
"""Unpacks coefs array into separate coefs matrixes"""
self.alpha, self.beta = self._coefs = flats_to_matrix(coefs)