#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Dec 30 20:02:22 2017

@author: Kamessi
"""

import csv
import numpy as np
from scipy import linalg as LA

def read_country(filename):
    f = open(filename,'r', encoding='utf-8')
    reader = csv.reader(f)
    raw_matrix = []
    for row in reader:
        temp = []
        for i in range(0,len(row)):
            try:
                temp.append(float(row[i]))
            except ValueError:
                temp.append(row[i])
        raw_matrix.append(temp)  
    f.close()
    return raw_matrix


def main():
    #Read the raw matrix
    raw_matrix = read_country("matrix2009.csv")
    
    #compute mcp
    product_list = raw_matrix[0][1::]
    country_list = []
    for i in range(1,len(raw_matrix)):
        country_list.append(raw_matrix[i][0])
    
    country_sum = []
    for i in range(1,len(raw_matrix)):
        country_sum.append(np.sum(raw_matrix[i][1::]))
    
    product_sum = []
    for i in range(1,len(raw_matrix[0])):
        product = 0
        for j in range(1,len(raw_matrix)):
            product += raw_matrix[j][i]
        product_sum.append(product)
    total_sum = np.sum(product_sum)
    
    mcp = []
    
    for i in range (1,len(raw_matrix)):
        country_row = []
        for j in range(1,len(raw_matrix[i])):
            percentage = raw_matrix[i][j]/country_sum[i-1]
            total_percentage = product_sum[j-1]/total_sum
            if percentage > total_percentage:
                country_row.append(1)
            else:
                country_row.append(0)
        mcp.append(country_row)
    
    #compute mcc
    mcp2 = mcp
    country_sum = []
    for i in range(0,len(mcp)):
        country_sum.append(np.sum(mcp[i]))
    
    product_sum = []
    for i in range(0,len(mcp[0])):
        product = 0
        for j in range(0,len(mcp)):
            product += mcp[j][i]
        product_sum.append(product)
    total_sum = np.sum(product_sum)
    print(total_sum)
    
    mcc = []
    for i in range(0,len(mcp)):
        country_row = []
        for j in range(0,len(mcp)):
            temp_sum = 0
            for k in range(0,len(mcp[0])):
                try:
                    value = (mcp[i][k] * mcp2[j][k]/(country_sum[i]*product_sum[k]))
                    if np.isinf(value) or np.isnan(value):
                        temp_sum += 0
                    else:
                        temp_sum += value
                except:
                    pass
            country_row.append(temp_sum)
        mcc.append(country_row)
    
    matrix = open("mcc.csv",'w',newline='')
    writer = csv.writer(matrix)
    for i in range(0,len(mcc)):
        writer.writerow(mcc[i])
    matrix.close()
    
    #compute and write ECI
    mcc = np.array(mcc)
    
    e_vals, e_vecs = LA.eig(mcc)
    eigenvectors = e_vecs.tolist()
    eigen = []
    for eigenvector in eigenvectors:
        temp = []
        for col in eigenvector:
            temp.append(col.real)
        eigen.append(temp)
    
    vector = []
    for i in range(0,len(eigen)):
        vector.append(eigen[i][1])
    
    eci = []
    if vector[0] < 0:
        for item in vector:
            eci.append((item-np.mean(vector))/np.std(vector))
    else:
        for item in vector:
            eci.append((-item+np.mean(vector))/np.std(vector))
    
    matrix = open("eci_original.csv",'w',newline='')
    writer = csv.writer(matrix)
    for i in range(0,len(eci)):
        writer.writerow([country_list[i],eci[i]])
    matrix.close()
    

if __name__ == "__main__":
    main()