import pandas as pd
import xlsxwriter
from random import uniform
import math
import numpy as np


def calucateMean(df) -> tuple:
    mean = []
    maximum = []
    minimum = []
    for col in range(df.shape[1]):  # 0 ta 10
        mean.append(0)
        maximum.append(0)
        minimum.append(math.inf)
        for row in df:
            if (row[col] > maximum[col]):
                maximum[col] = row[col]
            if (row[col] < minimum[col]):
                minimum[col] = row[col]
            mean[col] += row[col]
        mean[col] = ((int)((mean[col] / len(df))*10000))/10000
    v = []
    for i in range(df.shape[1]):
        v.append(uniform(minimum[i], maximum[i]))
    vm = []
    for j in range(df.shape[1]):
        vm.append(mean[j] - v[j])
    return (mean, vm)


def matrixToxls(matrix, filename):
    workbook = xlsxwriter.Workbook(filename)
    worksheet = workbook.add_worksheet()
    row = 0
    for col, data in enumerate(matrix):
        worksheet.write_column(row, col, data)
    workbook.close()


def entropy(col):
    total = sum([row[col] for row in df])
    print(total)
    return [-(math.fabs(row[col]) / total*100) * math.log((math.fabs(row[col]) / total*100), 2) for row in df]


if __name__ == "__main__":
    df = pd.read_excel('dataset2.xls', sheet_name="forestfires").to_numpy()
    (mean, vm) = calucateMean(df)
    entropyMatrix = []
    for col in range(df.shape[1]):
        entropyMatrix.append(entropy(col))
    matrixToxls(entropyMatrix, "entropiesMatrix.xls")