import pandas as pd                                 # Data wrangling
import numpy as np                                  # Number handling
import matplotlib.pyplot as plt                     # Plotter handling
from scipy.integrate import odeint                  # Integral calculations

# Variables to control logging.
LOG: bool = True            # Log data to files
SCREEN: bool = True         # Log data to screen
DEBUG: bool = False         # More data to display

def read_data_file(data_file):
    data_frame = pd.read_csv(data_file)
    first_row_time = data_frame['Timestamp'].iloc[1]
    last_row_time = data_frame['Timestamp'].iloc[-1]
    first_row_value = data_frame['Value'].iloc[1]
    last_row_value = data_frame['Value'].iloc[-1]
    mean_value = data_frame['Value'].mean()
    median_value = data_frame['Value'].median()
    sum_value = data_frame['Value'].sum()

    if SCREEN:
        print('first_row_value ',first_row_value)
        print('last_row_value ',last_row_value)
        print('first_row_time ', first_row_time)
        print('last_row_time ', last_row_time)
        print('elapsed_time ', (last_row_time - first_row_time))
        print('mean_value ', mean_value)
        print('median_value ', median_value)
        print('sum_value ', sum_value)

    return data_frame

def plot_data_frame(data_file):

    data_frame = read_data_file(data_file)
    plt.plot(data_frame['Timestamp'], data_frame['Value'])
    # plt.savefig(data_file + '.png')
    # img = plt.imread(data_file + '.png')
    # plt.imshow(img)
    plt.show()

    plot_data_frame(data_file = 'pid-balancer_twin_test_data.csv')