import sys
import os

import argparse
import time
import datetime
import subprocess
import re
import csv
import time
import operator
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

#https://pandas.pydata.org/pandas-docs/stable/user_guide/visualization.html
#https://queirozf.com/entries/pandas-dataframe-plot-examples-with-matplotlib-pyplot

if sys.version_info[0] != 3:
    print("This script requires Python 3")
    exit(1)

if 'py-json' not in sys.path:
    sys.path.append(os.path.join(os.path.abspath('..'), 'py-json'))


class L3CSVParcer():
    def __init__(self,csv_file):


        # left this in
        '''csv_obj = open(csv_file, 'r')
        csv_reader = csv.reader(csv_obj)
        print(csv_reader)

        for row in csv_reader:
            if row[1] == 'rx':
                print(row)'''

        inclu = ['Time','LT','MLT']
        self.csv_file = csv_file
        df = pd.read_csv(self.csv_file,header = 0, usecols = lambda column : any(substr in column for substr in inclu)

        total_cols = len(df.axes[1])

        #print(total_cols)
        #self.df = pd.read_csv('longevity_results_08_12_2020_10_19.csv')
        #print("df:{}".format(df))

        #print(df.columns)

        #print(df.loc[df['Monitor'] == 'rx_delta'])
        #print(df.loc[df['Monitor'] == 'rx'])

        df_rx_delta = df.loc[df['Monitor'] == 'rx_delta']

        print(df_rx_delta.describe())

        df_rx_delta.plot(x='Time epoch', y='average_rx_data')
        plt.show()

        df_rx_drop_pct = df.loc[df['Monitor'] == 'rx_drop_percent']
        df_rx_delta.plot(x='Time epoch', y='average_rx_data')
        plt.show()


        df2 = df.filter(regex='LT-s')
        print(df2)
        #plt.plot(df2[0], df2[1]
        #plt.show()

        df2_mean = df2.mean().sort_values(ascending=False)

        print(df2_mean)

        df2_mean_no_outliers = df2_mean[df2_mean(df2_mean.quantile(.10), df2_mean.quantile(.90))]

        print("no outliers")
        print(df2_mean_no_outliers)

        print("Top 10")
        print(df2_mean.head(10))
        print("Bottom 10")
        print(df2_mean.tail(10))

        print("mean others")



        # set display format otherwise get scientific notation
        pd.set_option('display.float_format', lambda x: '%.3f' % x)

        df_mean = df_rx_delta.mean().sort_values()

        #print(df_mean)

        print(df_mean[0])




        #df_uni_cast = [col for col in df_rx_delta if 'LT' in col]
        #df_LT_rx_delta_mean = df_uni_cast.mean().sort_values()

        #print(df_LT_rx_delta_mean)
        x = np.linspace(0, 20, 100)
        plt.plot(x, np.sin(x))
        plt.show()



    



def main():

    debug_on = False
    parser = argparse.ArgumentParser(
        prog='quick_test.py',
        formatter_class=argparse.RawTextHelpFormatter,
        epilog='''\
 Useful Information:
            ''',
        
        description='''\
quick_test.py:

        ''')


    parser.add_argument('-i','--infile', help="file of csv data", default='longevity_results_08_14_2020_14_37.csv')
    parser.add_argument('--debug', help='--debug:  Enable debugging',default=True)


    args = parser.parse_args()

    debug_on = args.debug

    if args.infile:
        csv_file_name = args.infile

    l3_csv_analysis = L3CSVParcer(csv_file_name)



if __name__ == "__main__":
    main()