# -*- coding: utf-8 -*-
"""
Created on Tue Mar 10 14:51:01 2020

@author: Johan Rene van Dorp
"""

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

width = 0.5
time = np.arange(11)*width+17
temperature =np.array([43,43,41,41,41,42,43,58,58,41,41])

# Calculating the sample mean and the sample median
wick_data = pd.DataFrame({'Time':time, 'Temp':temperature})
wick_data = wick_data.sort_values(by=['Temp'])
mean_wick = wick_data.mean()
median_wick = wick_data.median()

# Calculating the sample standard deviation and the sample Median of Absolute Deviation (MAD)
sd_wick = wick_data.std()
abs_dev_wick = wick_data - median_wick
mad_wick = abs_dev_wick.median()
min_wick = wick_data.min()
max_wick = wick_data.max()

# Parameters for the plots
LB_x = min_wick['Time']
UB_x = max_wick['Time']
LB_y =  min_wick['Temp']
UB_y =  max_wick['Temp']

# Creating a figure with three panels horizontally and setting some figure parameters

plt.rc('font', family='serif', size='10')
plt.figure(figsize=(15, 5))
Wick_Figure = plt.figure()
Wick_Figure.set_figwidth(9)
Wick_Figure.set_figheight(4.5)
Wick_Figure.subplots_adjust(hspace=0.4, wspace=0.4)
plt.rcParams['xtick.labelsize'] = 8
plt.rcParams['ytick.labelsize'] = 8
off_set_x = 0.5
off_set_y = 2.5
x_lims = (LB_x-off_set_x,UB_x+off_set_x)
y_lims = (LB_y-off_set_y,UB_y+off_set_y)

# Plotting the Left Figure Panel

Panel = Wick_Figure.add_subplot(1,3,1)
plt.xlim(x_lims)
plt.ylim(y_lims)
plt.xlabel('Time')
plt.ylabel('Temperature')
plt.scatter(wick_data['Time'],wick_data['Temp'],color = "navy", s = 2)
plt.axhline(mean_wick['Temp'], lw=1, ls = ':',color = 'red',alpha=0.5)
plt.axhline(median_wick['Temp'], lw=1, ls = ':',color = 'green',alpha=0.5)
mu = mean_wick['Temp']
text_str ='$ \overline{x} = $' + f'{mu:3.2f}'
plt.text(20,mu+0.25,text_str,color = 'red', size = 8)
med = median_wick['Temp']
text_str ='$ \hat{x}_{0.5} = $' + f'{med:3.2f}'
plt.text(20,med-0.75,text_str,color = 'green', size = 8)

# Plotting the Middle Figure Panel

mean_wick = wick_data[0:9].mean()
median_wick = wick_data[0:9].median()

Panel = Wick_Figure.add_subplot(1,3,2)
plt.xlim(x_lims)
plt.ylim(y_lims)
plt.xlabel('Time')
plt.ylabel('Temperature')
plt.scatter(wick_data['Time'][0:9],wick_data['Temp'][0:9],color = "navy", s = 2)
plt.axhline(mean_wick['Temp'], lw=1, ls = ':',color = 'red',alpha=0.5)
plt.axhline(median_wick['Temp'], lw=1, ls = ':',color = 'green',alpha=0.5)
mu = mean_wick['Temp']
text_str ='$ \overline{x} = $' + f'{mu:3.2f}'
plt.text(20,mu+0.25,text_str,color = 'red', size = 8)
med = median_wick['Temp']
text_str ='$ \hat{x}_{0.5} = $' + f'{med:3.2f}'
plt.text(20,med-0.75,text_str,color = 'green', size = 8)

# Plotting the Right Figure Panel

temperature =np.array([43,43,41,41,41,42,43,42,42,39,39])
wick_data = pd.DataFrame({'Time':time, 'Temp':temperature})
wick_data = wick_data.sort_values(by=['Temp'])
mean_wick = wick_data.mean()
median_wick = wick_data.median()

Panel = Wick_Figure.add_subplot(1,3,3)
plt.xlim(x_lims)
plt.ylim(y_lims)
plt.xlabel('Time')
plt.ylabel('Temperature')
plt.scatter(wick_data['Time'],wick_data['Temp'],color = "navy", s = 2)
plt.axhline(mean_wick['Temp'], lw=1, ls = ':',color = 'red',alpha=0.5)
plt.axhline(median_wick['Temp'], lw=1, ls = ':',color = 'green',alpha=0.5)
mu = mean_wick['Temp']
text_str ='$ \overline{x} = $' + f'{mu:3.2f}'
plt.text(20,mu-0.75,text_str,color = 'red', size = 8)
med = median_wick['Temp']
text_str ='$ \hat{x}_{0.5} = $' + f'{med:3.2f}'
plt.text(20,med+0.25,text_str,color = 'green', size = 8)

Wick_Figure.suptitle('Wick Temperature Data',size='14')
plt.savefig('Wick_Temp.png', dpi=300)