- Author:
- WeiweiAi <wai484@aucklanduni.ac.nz>
- Date:
- 2022-06-13 12:35:09+12:00
- Desc:
- Update the documentation
- Permanent Source URI:
- https://models.cellml.org/workspace/83f/rawfile/309a2cd1708eb79e1e9f8b928b41c9d36bcb94fc/Simulation/src/plotFig4_ci.py
# importing modules
import sys as sys
import os
import pandas as pd
import matplotlib.pyplot as plt
# Getting the name of the directory where this file is present.
current = os.path.dirname(os.path.realpath(__file__)) # src
# Getting the parent directory name where the current directory is present.
parent = os.path.dirname(current) # Simulation
# Getting the grandparent directory name
gparent = os.path.dirname(parent) # SinglePASMC
# The path where the plotExp.py is saved
mpath = gparent + '\\cellLib\\Scripts'
# appending a path
sys.path.append(mpath)
import plotExp
# The properties of traces
colors=plt.rcParams['axes.prop_cycle'].by_key()['color']
lines = ['-','--','-.',':']
markers = ['.',',','o','+','x','d']
# Figure file name and titles
figfiles=parent+'\\simFig4_ci.png'
fig_title = 'Response of an isolated SMC provoked by 80 mM KCl'
plot_title =['$Ca^{2+}$ concentration in the cytosol']
labels = ['$c_{i0}=0.07997$,$s_{i0}=0.347$,$v_{i0}=-25$','$c_{i0}=0.07997$,$s_{i0}=0.347$,$v_{i0}=-45$','$c_{i0}=0.1$,$s_{i0}=1.06$,$v_{i0}=-28$','Original']
# Data source
dfile_original=parent+'\\originalData\\Fig4.csv'
dfolder_sim=parent+'\\simulatedData\\'
x_var_org ='x'
y_var_org ='Curve1'
x_var_sim = 't'
y_vars_sim = ['output/c_i']
x_label='t(s)'
y_label=['$c_{i}(\mu M)$']
# Build the traces
number_trace = 3
number_plot = len(y_vars_sim)
trace = [[0] * number_trace for i in range(number_plot)]
data = pd.read_csv(dfile_original)
x_data=data[x_var_org].values
y_data=data[y_var_org].values
trace_org={'dataX': x_data, 'dataY': y_data, 'lname': labels[number_trace], 'linestyle':lines[1], 'marker':None, 'linecolor':colors[number_trace],'y2':False}
for plotid, y_var_sim in enumerate(y_vars_sim):
for traceid in range(number_trace):
filename='simFig4_%s.csv' % (traceid+1)
dfile = dfolder_sim + filename
data = pd.read_csv(dfile)
x_data=data[x_var_sim].values
y_data=data[y_var_sim].values
trace[plotid][traceid]={'dataX': x_data, 'dataY': y_data, 'lname': labels[traceid], 'linestyle':lines[0], 'marker':None, 'linecolor':colors[traceid],'y2':False}
# Build the plots
# maxH=8.75 inches, width 2.63-7.5
rows,cols = 1,1
left = 0.125 # the left side of the subplots of the figure,0.125
right = 0.9 # the right side of the subplots of the figure,0.9
bottom = 0.1 # the bottom of the subplots of the figure, 0.1
top = 0.8 # the top of the subplots of the figure 0.9
wspace = 0.4 # the amount of width reserved for space between subplots,
# expressed as a fraction of the average axis width, 0.2
hspace = 0.6 # the amount of height reserved for space between subplots,
# expressed as a fraction of the average axis height, 0.2
lgdfont, labelfont =10, 10
width, height= cols*6, rows*5
figs ={ 'width':width, 'height': height, 'rows': rows, 'cols': cols,'left':left,'bottom':bottom,'right':right,'top':top,'wspace': wspace,'hspace': hspace,'fig_title':fig_title,'title_y':1}
plots=[]
for id in range(1):
colid = id%2
rowid = id//2
lgdshow = True
bbox_to_anchor = (1.1,1.25)
trace[id].append(trace_org)
iplot={'rowid':rowid, 'colid':colid, 'xlabel': x_label, 'ylabel':y_label[id], 'twiny':False, 'ylabel2':y_label[id],'labelcolor':colors[1],
'lgdshow': lgdshow, 'lgdloc':'best', 'bbox_to_anchor':bbox_to_anchor,'lgdncol': 2, 'lgdfont':lgdfont, 'labelfont': labelfont,
'setxlim': False, 'xmin':0, 'xmax': 1, 'setylim': False,'ymin':0, 'ymax':1, 'grid': True, 'gridaxis': 'both', 'plot_title': plot_title[id],
'traces':trace[id]
}
plots.append(iplot)
ids = range(len(y_vars_sim))
subfigs={ids: plots for ids, plots in zip(ids, plots)}
fig,axs=plotExp.plotExp(figs,subfigs,figfiles)
