import numpy as np
import gurobipy as gp
from gurobipy import GRB
from pynverse import inversefunc
import copy

def f(wi):
    y = wi**2
    return y

def g(wi):
    y = 2*wi
    return y


model = gp.Model("qp")
model.setParam("PSDTol", float('Inf'))

w = model.addVar(lb=-5, ub=5, name="w", vtype=GRB.CONTINUOUS)
v = model.addVar(lb=-5, ub=5, name="v", vtype=GRB.CONTINUOUS)

model.setObjective(v,GRB.MINIMIZE)#si deve minimizzare v

wi=-1
for i in range(20):
    #calcolo f(w) e g(w) con i pesi iniziali e poi quelli aggiornati
    fwi=f(wi)
    gwi=g(wi)

    #aggiunta vincolo quindi aggiornamento dei bundle
    contr =  v >= gwi*(w-wi)+fwi
    model.addConstr(contr, str(i))

    model.optimize()

    for v in model.getVars():
        #print variabili
        print('%s %g' % (v.varName, v.x))
        #aggiornamento pesi
        if(v.varName=="w"):
            wi=v.x
    #print funzione
    print('Obj: %g' % model.getObjective().getValue())

#wi punto di minimo trovato nel bundle
min_val=f(wi)
print("Valore di minimo finale")
print(min_val)





#######################################################################################
'''PRIMA PROVA
wi1=-1

fwi1=f(wi1)
gwi1=g(wi1)

partcontr =  v >= gwi1*(w-wi1)+fwi1

model.addConstr(partcontr, "sa")

wi2=5

fwi2=f(wi2)
gwi2=g(wi2)

partcontr =  v >= gwi2*(w-wi2)+fwi2

model.addConstr(partcontr, "s")

model.optimize()

for v in model.getVars():
    print('%s %g' % (v.varName, v.w))

print('Obj: %g' % model.getObjective().getValue())
'''