causalPartition.py [142:156]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
                    continue
                    # if (almost) positivity can't be satisfied
                    
                idxs_left = np.product([df[key] <= th for key, sign, th in rules if sign == 0] + \
                       [df[key] > th for key, sign, th in rules if sign == 1] + \
                        [df[feature] <= threshold],
                       axis=0) > 0

                idxs_right = np.product([df[key] <= th for key, sign, th in rules if sign == 0] + \
                       [df[key] > th for key, sign, th in rules if sign == 1] + \
                        [df[feature] > threshold],
                       axis=0) > 0

                left = df[idxs_left]
                right = df[idxs_right]
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



causalPartition.py [392:405]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
                    continue

                idxs_left = np.product([df[key] <= th for key, sign, th in rules if sign == 0] + \
                       [df[key] > th for key, sign, th in rules if sign == 1] + \
                        [df[feature] <= threshold],
                       axis=0) > 0

                idxs_right = np.product([df[key] <= th for key, sign, th in rules if sign == 0] + \
                       [df[key] > th for key, sign, th in rules if sign == 1] + \
                        [df[feature] > threshold],
                       axis=0) > 0

                left = df[idxs_left]
                right = df[idxs_right]
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -