Glitch - Element/Compound Optimiser

glitch-compound-optimiser.py

RED = 0
GREEN = 1
BLUE = 2
SHINY = 3

SELLING = 0
SUGGESTED = 1

class Compound():
    def __init__(self, elements, price, name):
        self.elements = elements #[R,G,B,S]
        self.price =  [float(i) for i in price] #[SUGGESTED, SELLING]
        self.name = name

class Powder():
    def __init__(self,compounds,price,name):
        self.compounds = compounds
        self.price = [float(i) for i in price] #[SUGGESTED, SELLING]
        self.name = name
        
        self.elements = [0,0,0,0] #R,G,B,S
        self.updateElements()
    def updateElements(self):
        for c,amount in self.compounds.iteritems():
            for i in range(4):
                self.elements[i] += amount*comp_dic[c].elements[i]

  

mabon = Compound([0, 7, 7, 7], [12, 15], 'mabon')
grendalinunin = Compound([17, 7, 4, 2], [9, 11], 'grendalinunin')
potoxin = Compound([7, 11, 4, 0], [8, 9], 'potoxin')
spriggase = Compound([11, 7, 5, 0], [7, 9], 'spriggase')
cosmox = Compound([12, 0, 4, 3], [7, 8], 'cosmox')
alphose = Compound([3, 5, 7, 0], [6, 8], 'alphose')
abbasidose = Compound([4, 2, 6, 0], [5, 6], 'abbasidose')
humbabol = Compound([0, 0, 1, 5], [5, 5], 'humbabol')
zillene = Compound([0, 5, 3, 1], [4, 5], 'zillene')
friendly_acid = Compound([10, 0, 5, 0], [4, 5], 'friendly_acid')
rubemycin = Compound([5, 3, 2, 1], [4, 4], 'rubemycin')
lemene = Compound([4, 3, 2, 1], [4, 4], 'lemene')
ixite = Compound([2, 3, 2, 1], [3, 4], 'ixite')
groddlene = Compound([6, 3, 0, 0],[2, 2], 'groddlene')
diabolic_acid = Compound([1, 1, 1, 0],[1, 1], 'diabolic_acid')
tiite = Compound([2, 0, 1, 0], [1, 1], 'tiite')

sparkly = Compound([5, 1, 4, 6], [6, 8], 'sparkly')

compounds = [mabon,grendalinunin,potoxin,spriggase,cosmox,alphose,abbasidose,humbabol,zillene,friendly_acid,rubemycin,lemene,ixite,groddlene,diabolic_acid,tiite,sparkly]
comp_dic = {}
for c in compounds:
    comp_dic[c.name] = c

EHSP = Powder({"humbabol":160,"groddlene":40,"zillene":175},                        [1600,   2000],   "EHSP")
FHSP = Powder({"mabon":20,"humbabol":55,"zillene":65},                              [800,   1000],   "FHSP")
Fertilidust = Powder({"cosmox":10,"potoxin":20,"humbabol":40},                      [400,    500],    "Fertilidust")
FertilidustLite = Powder({"potoxin":10,"humbabol":15},                              [160,    200],    "FertilidustLite")
KrazySalts = Powder({"ixite":11,"lemene":11,"tiite":11},                            [89,    111],    "KrazySalts")
NoNoPowder = Powder({"cosmox":11,"lemene":4},                                       [80,    100],    "NoNoPowder")
PowderMildFecundity = Powder({"rubemycin":45,"alphose":40},                         [400,    500],    "PowderMildFecundity")
PowderStartlingFecundity = Powder({"cosmox":50,"rubemycin":75,"grendalinunin":60},  [1200,   1500],   "PowderStartlingFecundity")
SneezePowder = Powder({"ixite":20,"tiite":65},                                      [120,    150],    "SneezePowder")
SparklePowder = Powder({"abbasidose":30,"spriggase":30},                            [360,    450],    "SparklePowder")

powders = [EHSP,FHSP,Fertilidust,FertilidustLite,KrazySalts,NoNoPowder,PowderMildFecundity,PowderStartlingFecundity,SneezePowder,SparklePowder]


sparklies = 0

###############################################
# Best use of Elements, in terms of compounds #
###############################################

from pulp import *


#reshape data... just to follow this example
#http://packages.python.org/PuLP/CaseStudies/a_blending_problem.html

q = 1000
if True:
    R_total = sparkly.elements[RED]*q
    G_total = sparkly.elements[GREEN]*q
    B_total = sparkly.elements[BLUE]*q
    S_total = sparkly.elements[SHINY]*q
else:
    R_total = q*5000
    G_total = q*896
    B_total = q*3056
    S_total = q*46

price_style = SELLING

Comp_Names = []

price_dic = {}
r_dic = {}
g_dic = {}
b_dic = {}
s_dic = {}

for c in compounds:
    Comp_Names.append(c.name)
    price_dic[c.name] = c.price[price_style]
    r_dic[c.name] = c.elements[RED]
    g_dic[c.name] = c.elements[GREEN]
    b_dic[c.name] = c.elements[BLUE]
    s_dic[c.name] = c.elements[SHINY]

for c in powders:
    Comp_Names.append(c.name)
    price_dic[c.name] = c.price[price_style]
    r_dic[c.name] = c.elements[RED]
    g_dic[c.name] = c.elements[GREEN]
    b_dic[c.name] = c.elements[BLUE]
    s_dic[c.name] = c.elements[SHINY]

prob = LpProblem("Glitch Elements - Compund", LpMaximize)

compound_vars = LpVariable.dicts("Comps",Comp_Names,0,None,LpInteger)

# The objective function is added to 'prob' first
prob += lpSum([price_dic[i]*compound_vars[i] for i in Comp_Names]), "Total Selling Price for a Set of Compounds"

# The five constraints are added to 'prob'
prob += lpSum([r_dic[i]*compound_vars[i] for i in Comp_Names]) <= R_total, "Reds"
prob += lpSum([g_dic[i]*compound_vars[i] for i in Comp_Names]) <= G_total, "Greens"
prob += lpSum([b_dic[i]*compound_vars[i] for i in Comp_Names]) <= B_total, "Blues"
prob += lpSum([s_dic[i]*compound_vars[i] for i in Comp_Names]) <= S_total, "Shinies"

# The problem data is written to an .lp file
prob.writeLP("GlitchCompoundModel.lp")

# The problem is solved using PuLP's choice of Solver
prob.solve()

# The status of the solution is printed to the screen
print "Status:", LpStatus[prob.status]

# Each of the variables is printed with it's resolved optimum value
for v in prob.variables():
    print v.name, "=", v.varValue

# The optimised objective function value is printed to the screen
print "Total Selling Price for a Set of Compounds = ", value(prob.objective)
# The optimised objective function value is printed to the screen
print "Price Increase over Sparkly rock", value(prob.objective)/(q*sparkly.price[price_style])