- Author:
- WeiweiAi <wai484@aucklanduni.ac.nz>
- Date:
- 2021-07-06 11:22:35+12:00
- Desc:
- Change the figures size to fit the Physiome paper;
Adjust the solver setting to remove the notch in Fig6.
Minor editting in README.
- Permanent Source URI:
- https://staging.physiomeproject.org/workspace/692/rawfile/b98a10f69ee76a70243efdb648c598db5a866a2c/Simulation/Fig2_plot.py
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# The prefix of the saved output file name
filename = 'simFig2'
# Figure name
prefig = 'Fig2'
figfile = 'sim%s' % prefig
# Set figure dimension (width, height) in inches.
fw, fh = 6, 6
fig = plt.figure(figsize=(fw,fh))
# Set subplots
subpRow, subpCol = 1, 1
ax, lns = {}, {}
# 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 = 12, 12 # legend, label fontsize
# Read data from the files
x_name = 'V'
y_name = ['ICaL']
current= r'$I_{CaL}$'
y_labels = ['Normalized Current %s' % current]
Cai=[5.38843941249284e-5, 0.11]
T=297
for i, varName in enumerate(y_name):
ax[i] = fig.add_subplot(subpRow, subpCol, i+1)
n=0
ifilename = '%s_%d.csv' % (filename,n)
data = pd.read_csv(ifilename)
x_data = data[x_name]
y_data = data[varName]
ny_data=y_data/max(abs(y_data))
Ca=Cai[n] *100000
ax[i].plot(x_data, ny_data, color=cycle[n+1], label = '@$Ca_i$=%.2f nM, T=%dK' % (Ca,T))
n=n+1
ifilename = '%s_%d.csv' % (filename,n)
data = pd.read_csv(ifilename)
x_data = data[x_name]
y_data = data[varName]
ny_data=y_data/max(abs(y_data))
ax[i].plot(x_data, ny_data, color=cycle[n+1], label = '@$Ca_i$=%.2f mM, T=%dK' % (Cai[n],T))
ofilename ='fig2.csv'
odata = pd.read_csv(ofilename)
ox_data = odata['x']
oy_data = odata['Curve1']
ax[i].plot(ox_data, oy_data, '.', color=cycle[0], label = 'Poh_et_al_hJSMC')
plt.tick_params(direction='in', axis='both')
ax[i].legend(loc = 'best', fontsize=lfontsize, frameon=False)
ax[i].set_xlabel ('Voltage (mV)', fontsize= labelfontsize)
ax[i].set_ylabel (y_labels[i], fontsize= labelfontsize)
ax[i].set_title('%s in the primary publication' % (prefig))
figfiles = '%s.png' % (figfile)
plt.savefig(figfiles)
plt.show()
