# To plot the gating variables steady state and time constants

def steadyPlot(simFign,sedversions,outKeys):
   import numpy as np
   import matplotlib.pyplot as plt
   import pandas as pd
         
   # 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']
   cline = ['.','-.',':','--',]
   # Set subplots
   lfontsize, labelfontsize = 12, 12 # legend, label fontsize   
   # Read data from the files
   x_name = 'V'
   y_name = outKeys   
   y_label1 = y_name.replace('outputs/', '$')
   y_label = y_label1.replace('_inf', '_{\infty}$')  
   
   for i, varName in enumerate([y_name]):   
       ax[i] = fig.add_subplot(subpRow, subpCol, i+1) 
       for j, sedversion in enumerate(sedversions):
           # The saved output file name 
           filename = '../simulatedData/simVramp_%s.csv' % sedversion
           data = pd.read_csv(filename)
           x_data = data[x_name]
           y_data = data[varName]          
           ax[i].plot(x_data, y_data, cline[j], color=cycle[j+1], label = 'CellML_V%s' % sedversion)
   
       ofilename ='../originalData/%s.csv' %simFign
       odata = pd.read_csv(ofilename)
       ox_data = odata['x']   
       oy_data = odata['Curve1']    
       ax[i].plot(ox_data, oy_data, '.',  color=cycle[0], label = 'Testrow_et_al_2018')
   
       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_label, fontsize= labelfontsize)
       ax[i].set_title('%s in the primary publication' % (simFign))
       
   
   figfiles = '../sim%s.png' % (simFign)
   plt.savefig(figfiles)        
   plt.show()

def tauPlot(simFign, sedversions, outKeys,logflag,sflag):
   import numpy as np
   import matplotlib.pyplot as plt
   import pandas as pd
   # 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']
   cline = ['.','-.',':','--',]
   # Set subplots
   lfontsize, labelfontsize = 12, 12 # legend, label fontsize   
   # Read data from the files
   x_name = 'V'
   y_name = outKeys   
   y_label1 = y_name.replace('outputs/', '$\\')
   y_label1 = y_label1.replace('_', '_{')
   y_lable= y_label1+'}$'
   
   for i, varName in enumerate([y_name]):   
       ax[i] = fig.add_subplot(subpRow, subpCol, i+1)
       for j, sedversion in enumerate(sedversions):  
           # The saved output file name 
           filename = '../simulatedData/simVramp_%s.csv' % sedversion
           data = pd.read_csv(filename) 
           x_data = data[x_name]       
           if sflag==1:
               y_data = data[varName]/1000
               y_lable= y_label1+'}$ (s)'
           else:
               y_data = data[varName]
               y_lable= y_label1+'}$ (ms)'
           ax[i].plot(x_data, y_data, cline[j], color=cycle[j+1], label = 'CellML_V%s' % sedversion)
   
       ofilename ='../originalData/%s.csv' %simFign
       odata = pd.read_csv(ofilename)
       ox_data = odata['x']   
       oy_data = odata['Curve1']    
       ax[i].plot(ox_data, oy_data, '.',  color=cycle[0], label = 'Testrow_et_al_2018')
   
       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_lable, fontsize= labelfontsize)
       ax[i].set_title('%s in the primary publication' % (simFign))
       if logflag==1:
           ax[i].set_yscale('log')
   
   figfiles = '../sim%s.png' % (simFign)
   plt.savefig(figfiles)        
   plt.show()