from local_search import local_search
from local_search import compute_observation_error
from local_search import regression_model
from perturbations import melt
from perturbations import split
from utils import count_elements
from utils import copyData

def VNS(data,index,method,kMax):
    K = len(data)
    kmax = kMax
    k=1
    bestSolution = data.copy()
    B = regression_model(data,index,{})
    bestQuadError = 0
    for cluster in data:
        for obs in data[cluster]:
            bestQuadError += compute_observation_error(obs,B[cluster],index)

    iteration = 0
    while iteration < 50:
        result = local_search(data,index)
        quadError = result[0]
        print "Iteration", iteration , "k=", k , "iterLS=", result[1]
        if quadError < bestQuadError:
            k=1
            copyData(data,bestSolution)
            bestQuadError = quadError
            print "New best error: ", bestQuadError, " (", iteration, ")"
        else:
            k = k + 1
            if k == kmax:
							copyData(bestSolution,data)
							break

        copyData(bestSolution,data)
        if method==1:
            melt(data,index,k)
        elif method==2:
            split(data,index,k)
        iteration += 1

    return bestQuadError