# Author: Leyla Noroozbabaee
# Date: 12/09/2021
# To reproduce Figure 4 and 5 from original paper, the python file 'ICC_Lees_Green.py'
# should be run in the Python console in OpenCOR.
import matplotlib.pyplot as plt
from pathlib import Path
import pandas as pd

# Figure Name
prefig = 'Fig_4'

# To include the extracted data from the original paper
Fig4_Extracted_data = 1

# Set Subplot
fig, axs = plt.subplots(2, 4, figsize=(14, 7), facecolor='w', edgecolor='k')
fig.subplots_adjust(hspace =.25, wspace=.25)
axs = axs.ravel()
labelfontsize = 12

# Set Title
title = ['A  High-Cl(NaV)', 'B  High-Cl(NSV)','C  High-Cl(NSCa)','D  High-Cl(CaV)','E  High-Cl(NaV)','F  High-Cl(NSV)',
       'G  High-Cl(NSCa)', 'H High-Cl(CaV)']
for i in range(4):
    filename1 = 'Fig4_%da.csv' % (i + 1)
    data = pd.read_csv(filename1)
    Ca_i_Ano1 = data [ 'Ca_i' ]
    Vm_Ano1 = data [ 'Vm' ]
    filename2 = 'Fig4_%db.csv' % (i + 1)
    data = pd.read_csv(filename2)
    time = data ['time']
    Ca_i_no_Ano1 = data ['Ca_i']
    Vm_no_Ano1 = data [ 'Vm' ]
    axs[i].plot(time, Vm_Ano1, 'b', time, Vm_no_Ano1, 'r')
    axs[i + 4].plot(time, Ca_i_Ano1, 'b', time, Ca_i_no_Ano1, 'r')
    axs[i].set_title(str(title[i]))

    axs [ i ].set_xlim([ 0, 15 ])
    axs [ i + 4 ].set_xlim([ 0, 15 ])
    if i == 3 or i == 7:
        axs [ i ].plot(time, Vm_Ano1, 'b', time, Vm_no_Ano1, 'r')
        axs [ i + 4 ].plot(time, Ca_i_Ano1, 'b', time, Ca_i_no_Ano1, 'r')
        axs [ i ].set_xlim([ 5.1, 20.1 ])
        axs [ i + 4].set_xlim([ 5.1, 20.1 ])
    axs[i+4].set_title(str(title[i+4]))
    axs [i+4 ].set_xlabel('Time [ms]', fontsize=labelfontsize)

if Fig4_Extracted_data == 1:
    for i in range(8):
        filename0 = 'Fig4_origin_%da.csv' % (i + 1)
        data_folder = Path("Fig4_extracted_data")
        file0_to_open = data_folder / filename0
        data = pd.read_csv(file0_to_open)
        y_d0 = data [ 'Curve1' ]
        x_d0 = data [ 'x' ]
        filename = 'Fig4_origin_%db.csv' % (i + 1)
        file_to_open = data_folder / filename
        data = pd.read_csv(file_to_open)
        y_d = data [ 'Curve1' ]
        x_d = data [ 'x' ]
        if i == 3 or i == 7:
            axs [ i ].plot(5+x_d0, y_d0, 'b*')
            axs [ i ].plot(5+x_d, y_d, 'r*')
        elif i == 2 or i == 6:
            axs [ i ].plot(0.8+x_d0, y_d0, 'b*')
            axs [ i ].plot(0.8+x_d, y_d, 'r*')
        elif i == 0 :
            axs [ i ].plot(0.6+x_d0, y_d0, 'b*')
            axs [ i ].plot(0.6+x_d, y_d, 'r*')
        elif i == 5 :
            axs [ i ].plot(x_d0, y_d0, 'b*')
            axs [ i ].plot(0.9+x_d, y_d, 'r*')
        elif i == 4 :
            axs [ i ].plot(1+x_d0, y_d0, 'b*')
            axs [ i ].plot(x_d, y_d, 'r*')
        else:
            axs [ i ].plot(x_d0, y_d0, 'b*')
            axs [ i ].plot(x_d, y_d, 'r*')
    figfiles = '%s.png' % (prefig)
    plt.savefig(figfiles)

    figfiles = '%s.pdf' % (prefig)
    plt.savefig(figfiles)


axs [0].set_ylabel('Vm [mV]', fontsize=labelfontsize)
axs [4].set_ylabel('Ca ($\mu$M)', fontsize=labelfontsize)
figfiles = '%s.png' % (prefig)
plt.savefig(figfiles)
plt.show()