import xml.etree.cElementTree as ET

from makeTree import makeTree

from readData import readData

import numpy as np

import sys

def estimateData(data, root):

else: return estimateData(data, root.getRghtChld())

def TreeResult (data, root):

return r

#main body of the program for loading data, tree and

# estimating classes of the test data

args = iter(sys.argv)

next(args)

mdlName = ""

inputFileTr = ""

inputClassesTr = ""

inputFileTs = ""

inputClassesTs = ""

for item in args:

if item == "-m":

mdlName = next(args)

elif item == "-itr1":

inputFileTr = next(args)

elif item == "-itr2":

inputClassesTr = next(args)

elif item == "-its1":

inputFileTs = next(args)

elif item == "-its2":

inputClassesTs = next(args)

if inputFileTr.lower() == "" or inputClassesTr == "" or (mdlName.lower() != "test" and mdlName.lower() != "train"):# or inputFileTs.lower() == "" or inputClassesTs.lower() == "":

print("You have NOT entered one of the required inputs!")

sys.exit()

#inputFileTr = "X_train.txt"

#inputClassesTr = "y_train.txt"

#inputFileTs = "X_test.txt"

#inputClassesTs = "y_test.txt"

print("\nLoading saved tree ...")

tree = ET.ElementTree(file="trained_Tree.xml")

xmlRoot = tree.getroot()

root = makeTree(xmlRoot)

print("\nReading 1 set of data ...")

clases = readData(inputClassesTr)

data1 = readData(inputFileTr)

data1 = np.append(data1, clases, axis=1)

if inputClassesTs != "":

print("\nReading 2 set of data ...")

clases = readData(inputClassesTs)

data2 = readData(inputFileTs)

data2 = np.append(data2, clases, axis=1)

data = np.append(data1, data2, axis=0) if inputClassesTs != "" else data1

randIndx = np.load('invtRandData.npy') if (mdlName.lower() == "test") else np.load('randData.npy')

print("Estimating classes and calculating accuracy ...")

result = TreeResult (data[randIndx, :], root)

crrts = sum(result)

print("Accuracy of the model is = %0.2f" %(crrts / float(len(result))))