def _set_static_regression_attributes()

in orbit/template/ktr.py [0:0]

• 72 lines of code
• 12 McCabe index (conditional complexity)

    def _set_static_regression_attributes(self):
        # if no regressors, end here
        if self._num_of_regressors == 0:
            return

        for index, reg_sign in enumerate(self._regressor_sign):
            if reg_sign == "+":
                self._num_of_positive_regressors += 1
                self._positive_regressor_col.append(self.regressor_col[index])
                # used for 'pr_knot_loc' sampling in pyro
                self._positive_regressor_init_knot_loc.append(
                    self._regressor_init_knot_loc[index]
                )
                self._positive_regressor_init_knot_scale.append(
                    self._regressor_init_knot_scale[index]
                )
                # used for 'pr_knot' sampling in pyro
                self._positive_regressor_knot_scale_1d.append(
                    self._regressor_knot_scale[index]
                )
            elif reg_sign == "-":
                self._num_of_negative_regressors += 1
                self._negative_regressor_col.append(self.regressor_col[index])
                # used for 'nr_knot_loc' sampling in pyro
                self._negative_regressor_init_knot_loc.append(
                    self._regressor_init_knot_loc[index]
                )
                self._negative_regressor_init_knot_scale.append(
                    self._regressor_init_knot_scale[index]
                )
                # used for 'nr_knot' sampling in pyro
                self._negative_regressor_knot_scale_1d.append(
                    self._regressor_knot_scale[index]
                )
            else:
                self._num_of_regular_regressors += 1
                self._regular_regressor_col.append(self.regressor_col[index])
                # used for 'rr_knot_loc' sampling in pyro
                self._regular_regressor_init_knot_loc.append(
                    self._regressor_init_knot_loc[index]
                )
                self._regular_regressor_init_knot_scale.append(
                    self._regressor_init_knot_scale[index]
                )
                # used for 'rr_knot' sampling in pyro
                self._regular_regressor_knot_scale_1d.append(
                    self._regressor_knot_scale[index]
                )
        # regular first, then positive, then negative
        self._regressor_col = (
            self._regular_regressor_col
            + self._positive_regressor_col
            + self._negative_regressor_col
        )
        # numpy conversion
        self._positive_regressor_init_knot_loc = np.array(
            self._positive_regressor_init_knot_loc
        )
        self._positive_regressor_init_knot_scale = np.array(
            self._positive_regressor_init_knot_scale
        )
        self._positive_regressor_knot_scale_1d = np.array(
            self._positive_regressor_knot_scale_1d
        )
        self._negative_regressor_init_knot_loc = np.array(
            self._negative_regressor_init_knot_loc
        )
        self._negative_regressor_init_knot_scale = np.array(
            self._negative_regressor_init_knot_scale
        )
        self._negative_regressor_knot_scale_1d = np.array(
            self._negative_regressor_knot_scale_1d
        )
        self._regular_regressor_init_knot_loc = np.array(
            self._regular_regressor_init_knot_loc
        )
        self._regular_regressor_init_knot_scale = np.array(
            self._regular_regressor_init_knot_scale
        )
        self._regular_regressor_knot_scale_1d = np.array(
            self._regular_regressor_knot_scale_1d
        )