import numpy as np
from .travel_emission_linear_fit import EmissionModel as BaseEmissionModel


class EmissionModel(BaseEmissionModel):

    def apply_scaling_law(self, distance, config):

        assert config.points
        assert len(config.points) > 0

        footprint = None

        sample_points = sorted(config.points, key=lambda p: float(p[0]))

        # Numpy!

        previous_point = [0, 0]
        for i, sample_point in enumerate(sample_points):
            if distance <= sample_point[0]:
                t = 0
                if sample_point[0] != previous_point[0]:
                    t = (distance - previous_point[0]) * 1.0 \
                                       / \
                        (sample_point[0] - previous_point[0])

                footprint = previous_point[1] + t * (sample_point[1] - previous_point[1])
                previous_point = sample_point
                break

            previous_point = sample_point

        if footprint is None:
            if len(config.points) == 1:
                last = sample_points[0]
                penu = [0, 0]
            else:
                last = sample_points[-1]
                penu = sample_points[-2]

            t = 0
            if last[0] != penu[0]:
                t = (distance - last[0]) * 1.0 / (last[0] - penu[0])

            footprint = last[1] + t * (last[1] - penu[1])

        return footprint