import numpy as np

from point import *


class Knn:
    def __init__(self):
        self.space = np.array([])
    
    def reset(self):
        self.space = np.array([])

    def addPoint(self, coord, value):
        self.space = np.append(self.space, Point(coord, value))

    def getValueOfPoint(self, coord,nbNearest):
        points, dists = self.getNNearest(coord, nbNearest)
        ttPart = 1/(dists[0]+1)
        value = []
        for i in points[0].value:
            value.append(i * ttPart)
        for idx in range(1,len(points)):
            ttPart += 1/(dists[idx]+1)
            tvalue = points[idx].value
            for i in range(len(tvalue)):
                value[i] += tvalue[i] * (1/(dists[idx]+1))
        for i in range(len(value)):
            value[i] = value[i] / ttPart
        return value

    def getLabelOfPoint(self, coord,nbNearest):
        points, dists = self.getNNearest(coord, nbNearest)
        label = {}
        for idx in range(len(points)):
            tvalue = points[idx].value[0]
            if tvalue in label:
                label[tvalue] += 1/(dists[idx]+1)
            else:
                label[tvalue] = 1/(dists[idx]+1)
        value = max(label, key=label.get)
        return value

    def getNNearest(self, coord, nbNearest):
        dist = np.copy(self.space)
        dist = np.frompyfunc(lambda x: x.getDistFromCoord(coord), 1, 1)(dist)
        if (nbNearest > len(dist)):
            print("Error: not enough points")
            return None, None
        found = []
        distance = []
        for i in range(nbNearest):
            found.append(self.space[i])
            distance.append(dist[i])
        maxDistIdx = np.argmax(distance)
        for i in range(nbNearest, len(dist)):
            if (dist[i] < distance[maxDistIdx]):
                found[maxDistIdx] = self.space[i]
                distance[maxDistIdx] = dist[i]
                maxDistIdx = np.argmax(distance)
        return found, distance