- Author:
- WeiweiAi <wai484@aucklanduni.ac.nz>
- Date:
- 2021-09-30 13:14:32+13:00
- Desc:
- fix the typos and tables in doc
- Permanent Source URI:
- https://models.cellml.org/workspace/6bb/rawfile/5766fc294ca1fb80e47e776c78d754cad7f5fc7f/Simulation/src/Fig6_plot.py
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# The prefix of the saved output file name
prefilenames = ['simFig6']
ofilenames = ['fig6']
# Figure name
prefig = 'Fig6'
figfile = 'sim%s' % prefig
# Set figure dimension (width, height) in inches.
fw, fh = 6, 6
fig = plt.figure(figsize=(fw,fh))
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 = 11, 12 # legend, label fontsize
t_ss = [0]
# Read data from the files
x_name = 'time'
y_name = ["Cai", "V"]
y_labels = ['[Ca]$_i$ (nM)', 'Vm (mV)']
Nai=[ 16.55]
# Set subplots
subpRow, subpCol = len(y_name), 1
for h, plotN in enumerate(y_name):
if h ==0 :
ax[h] = fig.add_subplot(subpRow, subpCol, h+1)
ax[h].set_title('%s in the primary publication' % (prefig))
ofilename ='../originalData/%s.csv' % ofilenames[h]
odata = pd.read_csv(ofilename)
ox_data = odata['x']
oy_data = odata['Curve1']
ax[h].plot(ox_data, oy_data, '.', color=cycle[0], label = 'Bursztyn et al')
filename='../simulatedData/%s.csv' % (prefilenames[h])
data = pd.read_csv(filename)
x_data = data[x_name]
y_data = data[y_name[h]]*1000000
ax[h].plot(x_data, y_data, color=cycle[0], label = 'CellML model ' )
else:
ax[h] = fig.add_subplot(subpRow, subpCol, h+1)
filename='../simulatedData/%s.csv' % (prefilenames[h-1])
data = pd.read_csv(filename)
x_data = data[x_name]
y_data = data[y_name[h]]
ax[h].plot(x_data, y_data, color=cycle[0], label = 'V')
plt.tick_params(direction='in', axis='both')
ax[h].legend(loc = 'best', fontsize=lfontsize, frameon=False)
ax[h].set_xlabel ('Time (s)', fontsize= labelfontsize)
ax[h].set_ylabel (y_labels[h], fontsize= labelfontsize)
figfiles = '../%s.png' % (figfile)
plt.savefig(figfiles)
plt.show()
