owpolynomialregression.py 文件源码

def send_data(self):
        if self.data is not None:
            attributes = self.x_var_model[self.x_var_index]
            class_var = self.y_var_model[self.y_var_index]

            data_table = Table(
                Domain([attributes], class_vars=[class_var]), self.data)
            polyfeatures = skl_preprocessing.PolynomialFeatures(
                int(self.polynomialexpansion))

            valid_mask = ~np.isnan(data_table.X).any(axis=1)
            x = data_table.X[valid_mask]
            x = polyfeatures.fit_transform(x)
            x_label = data_table.domain.attributes[0].name

            out_array = np.concatenate((x, data_table.Y[np.newaxis].T[valid_mask]), axis=1)

            out_domain = Domain(
                [ContinuousVariable("1")] + ([data_table.domain.attributes[0]]
                                             if self.polynomialexpansion > 0
                                             else []) +
                [ContinuousVariable("{}^{}".format(x_label, i))
                 for i in range(2, int(self.polynomialexpansion) + 1)], class_vars=[class_var])

            self.Outputs.data.send(Table(out_domain, out_array))
            return

        self.Outputs.data.send(None)