Stage 3: Finding the tipping point In order to find the tipping point, i.e. the point at which the fire spreads much more substantially, we want to loop over many values of trees stsay, values from 0.01 to 1.0, in steps of 0.01) and run the model many times. If we keep track of the fraction of cells that are burned for each starting condition, we can show how burne nd Jtrees-sta late to each other The code below is incomplete, fill the missing code to below to make a plot to observe where the tipping point occurs In [16] board size 50 f tree[ _burned[l for tree fraction in # Complete this line game board on fire = True while on fireTrue: Complete this line game_board Complete this frac-empty on fire = line frac-empty, if frac-trees = frac-trees =-1.0: + # Complete this line E_tree.append (tree_fraction) f burned.append (frac_ empty (1.0-tree fraction) ) plt.plot(f_tree, f_burned) plt.xlabel ("tree fraction) plt.ylabel ( "burned fraction (normalized)) Pile "",line 6 for tree fraction in SyntaxError: invalid syntax Follow up task: Describe the model's behavior. Do you observe a "tipping point in sburnea That is, is there an abrupt change in behavior in Aburneas you increase ftrees_starDoes it agree with what you saw when you were experimenting with the NetLogo model? put your answer here