View difference between Paste ID: xgp7AnSf and K928gMzK

 from turtle import *
 # L-Systems 0.1.0
-#Version 0.0.5 by J.B. Wincek
+# By J.B. Wincek
-#The next version will be 0.1.0 which will be code clean up and comments
+
-#Changes from version 0.0.4: added in fractal Plant based grammar
+
 # These are the rules,grammars and alphabets for the differ L-Systems
 # They are organized by group and identified by the capitol letter
 
 # Algae
 axiomA='A'
 rulesA = {}
 rulesA['A'] = 'AB'
 rulesA['B'] = 'A'
 
 # Algae with the letters switched for testing perposes
 axiomB='B'
 rulesB = {}
 rulesB['B'] = 'BA'
 rulesB['A'] = 'B'
 
 # Kock curve
-turtleRulesF['F'] = 'forward(10)'
+
-turtleRulesF['+'] = 'left(90)'
+
-turtleRulesF['-'] = 'right(90)'
+
 turtleRulesF = {}
 turtleRulesF['F'] = 'forward(1)'
 turtleRulesF['+'] = 'left(85)'
 turtleRulesF['-'] = 'right(85)'
 
 # Sierpinkski triangle
 axiomS='A'
 rulesS = {}
 rulesS['A'] = 'B-A-B'
 rulesS['B'] = 'A+B+A'
 turtleRulesS = {}
 turtleRulesS['A'] = 'forward(3)'
 turtleRulesS['B'] = 'forward(3)'
 turtleRulesS['+'] = 'left(60)'
 turtleRulesS['-'] = 'right(60)'
 
-turtleRulesD['F'] = 'forward(3)'
+# Dragon curve
 axiomD='FX'
 rulesD={}
 rulesD['X']='X+YF'
 rulesD['Y']='FX-Y'
 turtleRulesD={}
 turtleRulesD['F'] = 'forward(7)'
 turtleRulesD['-'] = 'left(90)'
 turtleRulesD['+'] = 'right(90)'
 turtleRulesD['X'] = 'nul'
 turtleRulesD['Y'] = 'nul'
 
 # Fractal Plant
 axiomP='X'
 positionHash = ()
 positionHeap = []
 rulesP={}
 rulesP['X']='F-[[X]+X]+F[+FX]-X'
 rulesP['F']='FF'
 turtleRulesP={}
 turtleRulesP['F'] = 'forward(3)'
 turtleRulesP['-'] = 'left(25)'
 turtleRulesP['+'] = 'right(25)'
 turtleRulesP['X'] = 'nul'
 turtleRulesP['['] = """positionHeap.append(hashPosition())"""
 turtleRulesP[']'] = 'restorePosition(positionHeap.pop())'
 
 # these two methods are needed for storing the turles state
 def hashPosition():
     output = ()
     output = output + pos()
     output = (output, heading())
     return output
 def restorePosition(hashed):
     pu()
     setx(int(hashed[0][0]))
     sety(int(hashed[0][1]))
     setheading(hashed[1])
     pd()
     return hashed
 
 # this applies the rules to the current axiom (the input string)
 # format compose(<string>, <Dictionary>)
 def compose(axiom, rules):
         output = ""
         for i in axiom:
             output = output + rules.get(i,i)
         return output
 
 # the meat and potatoes of the genralized L system
 # format iterate(<string>,<dictionary>,<number>)
 # pass the starting condition as the axiom to this function
 def iterate(axiom,rules, times):
     output = ''
     if times == 0:
         output = axiom
     else:
-#print iterate(axiomA,rulesB,6)
+
-#print iterate(axiomB,rulesA,6)
+
-#directions = iterate(axiomF,rulesF,3)
+
-#print directions
+
 #                       <which rule set to use> ,
 #                       < which ruleset for turtle navigation> ,
 #                       <how many iterations>)
 def evaluate(axiom,rules,turtleRules,times):
     for words in iterate(axiom,rules,times):
-setx(200)
+
-sety(-200)
+
-left(90)
+
 
-color('red','yellow')
+
-#begin_fill()
+
 speed(0)
-#evaluate(axiomD,rulesD,turtleRulesD,14)
+
-#testString = "newHash = hashPosition()"
+setx(-350)
-#exec(testString)
+sety(-350)
-#print newHash
+
 # this adjusts the turtles starting angle
-evaluate(axiomP,rulesP,turtleRulesP,6)
+left(0)
 pd()
-#end_fill()
+color('pink','yellow')
 begin_fill()
 # these are examples of different rule sets, becareful high numbers will be slow
 #evaluate(axiomS,rulesS,turtleRulesS,6)
 evaluate(axiomF,rulesF,turtleRulesF,4)
 #evaluate(axiomP,rulesP,turtleRulesP,6)
 
 end_fill()
 done()
 
 #special thanks to http://www.4dsolutions.net/ocn/lsystems.html