import elkai
from algorithm.dataset import dmatrix, dmatrixLabel

INF=100000

#get subset matrix
def getSubset(dataset = [], sub=[]):
    subset = []
    for ridx in sub:
        subset.append( [dataset[ridx][x] for x in sub] )
    return subset


# #system input lables
# lables = ['C1', 'E2', 'E8', 'E4', 'C4', 'F2', 'D0', 'E9']

def getLabelIndex(lables, dmatrixLabel):
    sub = []
    for label in lables:
        if label in dmatrixLabel:
            sub.append(dmatrixLabel.index(label))
        else:
            raise Exception("Lable is not in data label matrix")
    return sub

#get two points distance
def getPoint2PointDistance(lables = []):
    #get distance matrix index
    sub = getLabelIndex(lables, dmatrixLabel)
    #get sub matrix
    subm = getSubset(dmatrix, sub)
    #return distance
    return subm[0][1]


def getItinerarys(lables = []):

    #get all matrix
    # sub = [ x for x in range(len(dmatrix)) ] 

    lables.sort()
    # print("getItinerarys: ", lables)

    #sub matrix index
    # sub = [1, 5, 7, 9, 10, 13, 15, 17]
    sub = getLabelIndex(lables, dmatrixLabel)

    # print("sub: ", sub)
    # #need to sort to the order same as dmatrix
    # sub.sort()
    # print("sub sort: ", sub)

    #get sub matrix
    subm = getSubset(dmatrix, sub)

    # print("sub matrix: ", subm)

    #init data matrix
    cities = elkai.DistanceMatrix(subm)
    #get tsp solved
    itinerarys = cities.solve_tsp()

    # print("itinerarys: ", itinerarys)

    tripNum = [ x for x in itinerarys ]
    # print("tripNum: ", tripNum)

    #get index
    trip = [ lables[x] for x in itinerarys ]
    #print result
    # print("trip: ", trip) # Output: [0, 2, 1, 0]

    return trip