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)