- 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/Fig10_plot.py
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# The prefix of the saved output file name
prefilenames = ['simFig10']
ofilenames = ['fig10A', 'fig10B']
# Figure name
prefig = 'Fig10'
figfile = 'sim%s' % prefig
# Set figure dimension (width, height) in inches.
fw, fh = 6, 8
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
# Read data from the files
x_name = ['time']
y_name = ['stress','Cai']
y_labels = ['(A) Stress (%)', '(B) [Ca]$_i$ (nM)']
x_labels = ['Time (s)','Time (s)',]
# Set subplots
subpRow, subpCol = len(y_name), 1
for h, plotN in enumerate(prefilenames):
for i in range(2):
ax[h*2+i] = fig.add_subplot(subpRow, subpCol, h*2+i+1)
ofilename ='../originalData/%s.csv' % (ofilenames[i])
odata = pd.read_csv(ofilename)
ox_data = odata['x']
oy_data = odata['Curve1']
ax[h*2+i].plot(ox_data, oy_data, '.', color=cycle[i], label = 'Bursztyn et al')
filename='../simulatedData/%s.csv' % (prefilenames[h])
data = pd.read_csv(filename)
x_data = data[x_name[h]]
if i ==1:
y_data = data[y_name[i]]*1000000
ax[h*2+i].set_xlabel (x_labels[i], fontsize= labelfontsize)
else:
y_data = data[y_name[i]]/0.8*100
ax[h*2+i].plot(x_data, y_data, color=cycle[i], label = 'CellML')
ax[h*2+i].set_ylabel (y_labels[i], fontsize= labelfontsize)
ax[h*2+i].legend(loc = 'best', fontsize=lfontsize, frameon=False)
if h+i == 0:
ax[h*2+i].set_title('%s in the primary publication' % (prefig))
plt.tick_params(direction='in', axis='both')
figfiles = '../%s.png' % (figfile)
plt.savefig(figfiles)
plt.show()
