- Author:
- Leyla <noroozbabaee@gmail.com>
- Date:
- 2021-11-17 16:24:01+13:00
- Desc:
- The final update of Yoast-2020.
- Permanent Source URI:
- https://staging.physiomeproject.org/workspace/7b5/rawfile/c7060d13dd45168e33fb9666440a421f84c24ab1/Simulations/Plot_Fig6.py
# Author: Leyla Noroozbabaee
# Date: 15/11/2021
# To reproduce Figure 6, execute 'Fig6_10_sim.py' & 'Fig6D_10D_sim.py' in the Python console in OpenCOR_.
# This can be done with the following commands at the prompt in the OpenCOR_ Python console:
# In [1]: cd path/to/folder_this_file_is_in
# In [2]: run Fig6_10_sim.py
import matplotlib.pyplot as plt
import pandas as pd
# Figure name
figfile = 'Fig6'
# Set figure dimension (width, height) in inches.
fw, fh = 15, 6
# Set subplots
subpRow, subpCol = 2, 2
ax, lns = {}, {}
# Set Title
tit = [' p=0.02 | p=0.05 | p=0.09 | p=0.25']
# This gives list with the colors from the cycle, which you can use to iterate over.
cycle = plt.rcParams['axes.prop_cycle'].by_key()['color']
# Set subplots
lfontsize, labelfontsize = 10, 14 # legend, label fontsize
fig, axs = plt.subplots(subpRow, subpCol, figsize=(fw, fh), facecolor='w', edgecolor='k')
fig.subplots_adjust(hspace = .2, wspace=.1)
data = pd.read_csv('ORAI_HEK.csv')
x_time = data ["time"]
HEK_ca_c = data ["ca_c"]
data = pd.read_csv('ORAI12_DKO.csv')
ORAI12_ca_c = data ["ca_c"]
axs[0,0].plot(x_time, HEK_ca_c, color='k', label='ORAI_HEK')
axs[0,0].plot(x_time, ORAI12_ca_c, color=cycle [ 8 % 7 ], label='ORAI12_DKO')
plt.tick_params(direction='in', axis='both')
axs [0,0].legend(loc='best', fontsize=lfontsize, frameon=False)
axs [0,0].set_ylabel('$ Ca_{c} (\mu M)$', fontsize=labelfontsize)
axs [0,0].set_title('%s' % (tit[0]))
axs [0,0].legend(loc='best', fontsize=lfontsize, frameon=False)
axs [0, 0].axis([ 0,200, 0, 0.8 ])
data = pd.read_csv('ORAI1_SKO.csv')
x_time = data ["time"]
ORAI1_ca_c = data ["ca_c"]
data = pd.read_csv('ORAI2_SKO.csv')
ORAI2_ca_c = data ["ca_c"]
axs[0, 1].plot(x_time, ORAI1_ca_c, color='r', label='ORAI1_SKO')
axs[0, 1].plot(x_time, ORAI2_ca_c, color='b', label='ORAI2_SKO')
axs[0, 1].set_title('%s' % (tit[0]))
axs[0, 1].legend(loc='best', fontsize=lfontsize, frameon=False)
axs[0, 1].axis([0, 200, 0, 0.8])
data = pd.read_csv('ORAI23_DKO.csv')
x_time = data ["time"]
ORAI23_ca_c = data ["ca_c"]
data = pd.read_csv('ORAI_TKO.csv')
ORAITKO_ca_c = data ["ca_c"]
axs[1, 0].plot(x_time, ORAI23_ca_c, color='g', label='ORAI23_DKO')
axs[1, 0].plot(x_time, ORAITKO_ca_c, color='gray', label='ORAI23_TKO')
axs[1, 0].legend(loc='best', fontsize=lfontsize, frameon=False)
axs[1, 0].set_ylabel('$Ca_{c}(\muM)$', fontsize=labelfontsize)
axs[1, 0].axis([0, 200, 0, 0.8 ])
axs[1, 0].set_xlabel('Time (s)', fontsize=labelfontsize)
f_name = ['ORAI_HEK','ORAI2_SKO', 'ORAI12_DKO','ORAI23_DKO']
clr = ['k', 'b', 'r','g']
for i in range(4):
file_name = '%s_D.csv' % f_name[i]
data = pd.read_csv(file_name)
ca_c = data [ "ca_c" ]
x_time = data [ "time" ]
axs [ 1, 1 ].plot(x_time, ca_c, color='%s' % clr[i] , label='%s ' % f_name[i])
axs [ 1, 1 ].legend(loc='center left', fontsize=lfontsize, frameon=False)
axs [1, 1 ].axis([ 0,250, 0, 1 ])
axs [1,1].set_xlabel('Time (s)', fontsize=labelfontsize)
figfiles = '%s_6.png' % figfile
plt.savefig(figfiles)
plt.show()
