Kwa msingi, chombo hiki kitatusaidia kupata thamani za mabadiliko ambayo yanahitaji kutimiza masharti fulani na kuhesabu kwa mkono kutakuwa na usumbufu mkubwa. Hivyo, unaweza kuonyesha kwa Z3 masharti ambayo mabadiliko yanahitaji kutimiza na itapata baadhi ya thamani (ikiwa inawezekana).
#pip3 install z3-solverfrom z3 import*s =Solver()#The solver will be given the conditionsx =Bool("x")#Declare the symbos x, y and zy =Bool("y")z =Bool("z")# (x or y or !z) and ys.add(And(Or(x,y,Not(z)),y))s.check()#If response is "sat" then the model is satifable, if "unsat" something is wrongprint(s.model())#Print valid values to satisfy the model
Ints/Simplify/Reals
from z3 import*x =Int('x')y =Int('y')#Simplify a "complex" ecuationprint(simplify(And(x +1>=3, x**2+ x**2+ y**2+2>=5)))#And(x >= 2, 2*x**2 + y**2 >= 3)#Note that Z3 is capable to treat irrational numbers (An irrational algebraic number is a root of a polynomial with integer coefficients. Internally, Z3 represents all these numbers precisely.)#so you can get the decimals you need from the solutionr1 =Real('r1')r2 =Real('r2')#Solve the ecuationprint(solve(r1**2+ r2**2==3, r1**3==2))#Solve the ecuation with 30 decimalsset_option(precision=30)print(solve(r1**2+ r2**2==3, r1**3==2))
Kuchapisha Mfano
from z3 import*x, y, z =Reals('x y z')s =Solver()s.add(x >1, y >1, x + y >3, z - x <10)s.check()m = s.model()print ("x = %s"% m[x])for d in m.decls():print("%s = %s"% (d.name(), m[d]))
Hesabu ya Mashine
CPUs za kisasa na lugha za programu za kawaida hutumia hesabu juu ya bit-vectors zenye ukubwa wa fasta. Hesabu ya mashine inapatikana katika Z3Py kama Bit-Vectors.
from z3 import*x =BitVec('x', 16)#Bit vector variable "x" of length 16 bity =BitVec('y', 16)e =BitVecVal(10, 16)#Bit vector with value 10 of length 16bitsa =BitVecVal(-1, 16)b =BitVecVal(65535, 16)print(simplify(a == b))#This is True!a =BitVecVal(-1, 32)b =BitVecVal(65535, 32)print(simplify(a == b))#This is False
Signed/Unsigned Numbers
Z3 inatoa toleo maalum la shughuli za kihesabu ambapo ina umuhimu ikiwa bit-vector inachukuliwa kama signed au unsigned. Katika Z3Py, waendeshaji <, <=, >, >=, /, % na >> wanalingana na toleo la signed. Waendeshaji wa unsigned husika ni ULT, ULE, UGT, UGE, UDiv, URem na LShR.
from z3 import*# Create to bit-vectors of size 32x, y =BitVecs('x y', 32)solve(x + y ==2, x >0, y >0)# Bit-wise operators# & bit-wise and# | bit-wise or# ~ bit-wise notsolve(x & y ==~y)solve(x <0)# using unsigned version of <solve(ULT(x, 0))
Functions
Kazi za tafsiri kama za hesabu ambapo kazi + ina tafsiri ya kawaida isiyobadilika (inaongeza nambari mbili). Kazi zisizo na tafsiri na constants ni za kiwango cha juu cha kubadilika; zinaruhusu tafsiri yoyote ambayo ni sawa na vizuizi juu ya kazi au constant.
Mfano: f inatumika mara mbili kwa x inarudi x tena, lakini f inatumika mara moja kwa x ni tofauti na x.
from z3 import*x =Int('x')y =Int('y')f =Function('f', IntSort(), IntSort())s =Solver()s.add(f(f(x)) == x, f(x) == y, x != y)s.check()m = s.model()print("f(f(x)) =", m.evaluate(f(f(x))))print("f(x) =", m.evaluate(f(x)))print(m.evaluate(f(2)))s.add(f(x) ==4)#Find the value that generates 4 as responses.check()print(m.model())
Mifano
Msolvesudoku
# 9x9 matrix of integer variablesX = [ [ Int("x_%s_%s"% (i+1, j+1))for j inrange(9) ]for i inrange(9) ]# each cell contains a value in {1, ..., 9}cells_c = [ And(1<= X[i][j], X[i][j] <=9)for i inrange(9)for j inrange(9) ]# each row contains a digit at most oncerows_c = [ Distinct(X[i])for i inrange(9) ]# each column contains a digit at most oncecols_c = [ Distinct([ X[i][j] for i inrange(9) ])for j inrange(9) ]# each 3x3 square contains a digit at most oncesq_c = [ Distinct([ X[3*i0 + i][3*j0 + j]for i inrange(3) for j inrange(3) ])for i0 inrange(3)for j0 inrange(3) ]sudoku_c = cells_c + rows_c + cols_c + sq_c# sudoku instance, we use '0' for empty cellsinstance = ((0,0,0,0,9,4,0,3,0),(0,0,0,5,1,0,0,0,7),(0,8,9,0,0,0,0,4,0),(0,0,0,0,0,0,2,0,8),(0,6,0,2,0,1,0,5,0),(1,0,2,0,0,0,0,0,0),(0,7,0,0,0,0,5,2,0),(9,0,0,0,6,5,0,0,0),(0,4,0,9,7,0,0,0,0))instance_c = [ If(instance[i][j] ==0,True,X[i][j] == instance[i][j])for i inrange(9)for j inrange(9) ]s =Solver()s.add(sudoku_c + instance_c)if s.check()== sat:m = s.model()r = [ [ m.evaluate(X[i][j])for j inrange(9) ]for i inrange(9) ]print_matrix(r)else:print"failed to solve"
