content: # -*- coding: utf-8 -*-
  from numpy import float32
  from numpy import linspace
  from numpy import polyfit
  from numpy import polyval
  import matplotlib.pyplot as plt
  
  #Read in data from csv
  f=open('data.csv','r')
  line=f.readlines()
  
  #Empty array for data
  FN=[]
  EFN=[]
  #This loop goes through every line, strips new line character and then splits the data on ,.  It will then save data into the arrays
  for l in line:
      a=l.strip()
      x,y=a.split(",")
      FN.append(float32(x))
      EFN.append(float32(y))
  f.close()
  
  #Generate linear space but this was not used as of yet  
  z=linspace(-1,4)
  
  #Create grid and plot data
  fig = plt.figure(figsize = (4,4), dpi = 600)
  a = fig.add_subplot(1,1,1)
  
  plt.plot(FN,EFN,'ks',markersize=3)
  
  #Created a fitted line for the data
  fit=polyfit(FN,EFN,1)
  plt.plot(z,polyval(fit,z),label=fit,color='k')
  
  #Reset font size
  for t in a.yaxis.get_major_ticks():
      t.label.set_fontsize(6)
  for t in a.xaxis.get_major_ticks():
      t.label.set_fontsize(6)
  
  #Set the subplot sizing
  fig.subplots_adjust(top=0.95, right =0.89, left=0.13,bottom=0.25)
  #Set limits and labels
  plt.xlim(-0.2,3.5)
  plt.ylim(0,0.8)
  plt.ylabel(r'Extrafloral Nectar (mg of sugar per extrafloral nectary)',fontsize=6,verticalalignment='center')
  plt.xlabel(r'Floral Nectar (mg of sugar per flower)',fontsize=6,horizontalalignment='center')
  
  #Save as pdf
  fig.savefig('EFNvFN.pdf',dpi=600)
  
  plt.show()
  
  """In ecology, animals and plants interact with one another in an ecosystem.  
  There are several types of interactions that may occur such as predation, 
  parasitisim and mutualism. Mutualism is where the animals and plants both give 
  one another a survival benefit.  So if a trait is not useful why invest energy 
  into producing it?
   
  Different interactions have generally been studied individually even though
  they occur in a community. This plot shows the relationship between EFN and FN 
  production in T. ulmifolia. There is a positive correlation, which suggests that 
  plants that produce more of one also produce more of the other
  This is probably because of overall plant vigour. This was an initial figure
  for a later experiment showing interactions."""
  