Location: Computational analysis of the human sinus node action potential @ 7c8af54fa19b / Fig4-plot.py

Author:
nima <nafs080@aucklanduni.ac.nz>
Date:
2021-06-10 08:38:04+12:00
Desc:
minor change
Permanent Source URI:
https://staging.physiomeproject.org/workspace/648/rawfile/7c8af54fa19b6744d5767ececd5af471d82e77a1/Fig4-plot.py

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import sys
# import plot_func
# reload (plot_func)
import os

data = pd.read_csv('Fig04.csv')


X1 = data[data.keys()[5]]*1000
Y1 = data[data.keys()[0]]
Y2 = data[data.keys()[1]]
Y3 = data[data.keys()[2]]
Y4 = data[data.keys()[3]]
Y5 = data[data.keys()[4]]





plt.figure(figsize=(14,12))

plt.plot(X1, Y1, 'navy',linestyle='-',  label = 'Control', linewidth= 3)
plt.plot(X1, Y2, 'red',linestyle='-',  label = 'Block 30%', linewidth= 3)
plt.plot(X1, Y3, 'green',linestyle='-',  label = 'Block 70%', linewidth= 3)
plt.plot(X1, Y4, 'purple',linestyle='-',  label = 'Block 90%', linewidth= 3)
plt.plot(X1, Y5, 'black',linestyle='-',  label = 'Block 100%', linewidth= 3)


plt.grid()
plt.xlim(0, 1900)
plt.ylim(-60,30)
plt.xticks(np.arange(0,1900, 200))
plt.yticks(np.arange(-60,35, 10))
plt.xlabel ('Time (ms)',fontsize=16)
plt.tick_params(axis='both', labelsize=14)
plt.ylabel ('V$_m$ (mV)', fontsize=16)
# plt.title('A')
plt.legend(bbox_to_anchor=(0.3, 0.9, 0.2, 0.07), loc='best',fontsize=14,
       ncol=1, mode="expand", borderaxespad=0.)


plt.tight_layout(pad=0.4, w_pad=0.5, h_pad=1.0)
plt.savefig('C:/Nima/ABI/Physiome Journal/sinus/Python_codes/figure4.png')
plt.show()
#~ plt.legend(loc=0)