# -*- coding: utf-8 -*-
"""
Created on Tue Mar 10 08:01:50 2020

@author: Johan Rene van Dorp
"""
import numpy as np
import matplotlib.pyplot as plt

data = np.array([4,3,9,1,7])
data.sort()
n_data = len(data)
ecdf = np.arange(1,n_data+1)/n_data

off_set_x = 2
data = np.append(min(data)-off_set_x,data)
data = np.append(data,max(data)+off_set_x)

ecdf = np.append(0,ecdf)
ecdf = np.append(ecdf,1)

# Creating the cumulative distribution figure
plt.rc('font', family='serif', size='10')
plt.figure(figsize=(10, 5))
CDF_figure = plt.figure()

# Adding the left panel with the theoretical pmf
Panel = CDF_figure.add_subplot(1,1,1)
Panel.axhline(1, lw=1, ls = ':',color = 'darkgray',alpha = 0.5)
plt.xlim((-0.5,10.5))
plt.ylim((-0.05,1.1))
plt.xlabel('x')
plt.ylabel('Empirical CDF $ \hat{F}(x) = Pr(X \leq x)$')
plt.title('Empirical CDF Example')
plt.axvline(0, lw=2, ls = '-',color = 'lightgray',alpha=0.5)
plt.axhline(0, lw=2, ls = '-',color = 'lightgray',alpha=0.5)
text_str = 'n = '+ str(n_data)
plt.text(4.75,0.9,text_str,color = 'red')

the_col = 'IndianRed'
x = data
y = ecdf
closed_x = x
closed_y = y
open_x = x[1:len(x)-1]
open_y = y[0:len(y)-2]
Panel.scatter(closed_x,closed_y,color = the_col)
Panel.scatter(open_x,open_y,edgecolor = the_col,facecolor = 'white') 
Panel.vlines(open_x, open_y, closed_y[1:len(closed_y)-1], color='black', linestyles=':', lw=1)
Panel.hlines(closed_y[0:len(closed_y)-1], closed_x[0:len(closed_x)-1],
                    closed_x[1:len(closed_x)], linestyles='-', lw=2,color = the_col)
plt.savefig('ECDF_Example.png', dpi=1200)