in orbit/template/ktr.py [0:0]
def _set_default_args(self):
"""Set default attributes for None"""
# default checks for seasonality and seasonality_fs_order will be conducted
# in ktrlite model and we will extract them from ktrlite model directly later
if self.coef_prior_list is not None:
self._coef_prior_list = deepcopy(self.coef_prior_list)
# if no regressors, end here #
if self.regressor_col is None:
# regardless of what args are set for these, if regressor_col is None
# these should all be empty lists
self._regressor_sign = list()
self._regressor_init_knot_loc = list()
self._regressor_init_knot_scale = list()
self._regressor_knot_scale = list()
return
def _validate_params_len(params, valid_length):
for p in params:
if p is not None and len(p) != valid_length:
raise IllegalArgument(
"Wrong dimension length in Regression Param Input"
)
# regressor defaults
num_of_regressors = len(self.regressor_col)
_validate_params_len(
[
self.regressor_sign,
self.regressor_init_knot_loc,
self.regressor_init_knot_scale,
self.regressor_knot_scale,
],
num_of_regressors,
)
if self.regressor_sign is None:
self._regressor_sign = [DEFAULT_REGRESSOR_SIGN] * num_of_regressors
if self.regressor_init_knot_loc is None:
self._regressor_init_knot_loc = [
DEFAULT_COEFFICIENTS_INIT_KNOT_LOC
] * num_of_regressors
if self.regressor_init_knot_scale is None:
self._regressor_init_knot_scale = [
DEFAULT_COEFFICIENTS_INIT_KNOT_SCALE
] * num_of_regressors
if self.regressor_knot_scale is None:
self._regressor_knot_scale = [
DEFAULT_COEFFICIENTS_KNOT_SCALE
] * num_of_regressors
self._num_of_regressors = num_of_regressors