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utils.py
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from math import perm
import qsimov as qj
import circuitos as ct
import random as rnd
import itertools
import copy
# Funcion que recibe un tiempo en segundos y lo formatea
def timeConversion(tiempo):
horas = int(tiempo / 60 / 60)
tiempo -= horas * 60 * 60
minutos = int(tiempo / 60)
tiempo -= minutos * 60
if (horas > 1):
return str(horas) + ' hora(s), ' + str(minutos) + ' minuto(s) ' + str(tiempo) + ' segundos'
elif (minutos > 1):
return str(minutos) + ' minuto(s) ' + str(tiempo) + ' segundos'
else:
return str(tiempo) + ' segundos'
# Obtiene los resultados de la medicion como simulador y formatea el resultado
def returnValues(values):
result = []
for i in range(len(values)):
if (values[i] > 10**(-25)):
result.append(str(i) + ': ' + str((values[i] * 100).round(2)))
else:
result.append(str(i) + ': 0')
return result
# Recibe un grafo y aplica el algoritmo n veces. Luego hace la media de los porcentajes
def iteratePhaseAlgorithm(graph, rotation, iterations, nGraphs):
output = []
executer = qj.Drewom(extra={'return_struct':False})
for _ in range(nGraphs):
algoritmoFase = ct.phaseAlgorithm(graph, rotation)
circuito = executer.execute(algoritmoFase, iterations)
output.append(frequency(circuito, iterations))
return output
# Devuelve el porcentaje correspondiente a cada valor
def frequency(circuit, iterations):
invertedList = []
for i in circuit: # Invierte los valores de la lista y los pasa a binario
aux = ''
for j in i:
if (j == True):
aux = aux + f'{1}'
else:
aux = aux + f'{0}'
invertedList.append(int(aux,2))
result = {}
maximo = max(invertedList) # Obtiene la frecuencia por elemento
for i in range(maximo + 1):
result[i] = 0
for j in invertedList:
if (i == j):
result[i] = result[i] + 1
for i in range(len(result)): # Pasa la frecuencia a porcentaje
result[i] = result[i]/iterations * 100
return result
# Coge la matriz a la que se le ha eliminado el nodo y se eliminan los valores
def updateMatrix(matrix, index):
matrix.pop(index)
for i in range(index):
for j in range(len(matrix[i])):
if (j == index):
matrix[i].pop(j)
return matrix
def randomMatrixGenerator(nNodes, cut=False):
# Se genera la matriz de 0
m = []
for i in range(nNodes):
m.append([])
for _ in range(nNodes):
m[i].append(0)
# Se añaden 1 aleatorios menos en la diagonal principal
for i in range(len(m)):
for j in range(len(m[i])):
if (i is not j):
if(rnd.random() >= 0.5):
m[i][j] = 1
if cut:
return m
else:
# Se devuelve la mitad de la matriz para que sea simetrica
return cutHalfMatrix(m)
# Recibe una matriz y devuelve la parte superior
def cutHalfMatrix(matrix):
count = 0
for i in range(len(matrix)):
matrix[i] = matrix[i][count:]
count += 1
return matrix
def getPermutationMatrix(nodes):
# Se genera la matriz de 0
m = []
for i in range(nodes):
m.append([])
for _ in range(nodes):
m[i].append(0)
for i in range(len(m)):
if ((i+1) == nodes):
m[i][0] = 1
else:
m[i][i+1] = 1
return m
def getTransposeOfMatrix(matrix):
transpose = []
for i in range(len(matrix)):
transpose.append([])
for j in range(len(matrix[i])):
transpose[i].append(matrix[j][i])
return transpose
def multiplyMatrices(m1, m2):
result = []
for i in range(len(m1)):
result.append([])
for j in range(len(m2[0])):
result[i].append(0)
for k in range(len(m1[0])):
result[i][j] += m1[i][k] * m2[k][j]
return result
def permuteMatrix(matrix):
permutation = getPermutationMatrix(len(matrix))
transpose = getTransposeOfMatrix(permutation)
p1 = multiplyMatrices(matrix, permutation)
p2 = multiplyMatrices(p1, transpose)
return p2
# Devuelve todas las posibles combinaciones de matrices de adyacencia dado un número de nodos
def getAllCombinations(nodes):
return [list(i) for i in itertools.product([0, 1], repeat=int((nodes*nodes - nodes)/2))]
# Funcion que devuelve todas las posibles matrices de adyacencia dado un número de nodos
def getAllMatrices(nodes):
lst = getAllCombinations(nodes)
m = randomMatrixGenerator(nodes, False)
matrices = []
for i in lst:
aux = copy.deepcopy(m)
for j in aux:
if (len(aux) > 1):
for k in range(1, len(j)):
j[k] = i.pop(0)
matrices.append(aux)
return matrices
# Para almacenar todos los grafos que se vayan a probar
prueba = [[0,1,1,0],[0,0,1],[0,1],[0]]
prueba2 = [ [0,1,1,0],
[1,0,0,1],
[1,0,0,1],
[0,1,1,0]]
docMatrix = [[0,1,1,1,0],[0,0,0,1],[0,0,1],[0,1],[0]]
M1 = [[0,0,0,0,0,1,1,0,0,1],
[0,0,1,1,0,0,0,0,0,1],
[0,1,0,1,1,0,1,1,1,1],
[0,1,1,0,1,1,1,1,0,0],
[0,0,1,1,0,1,0,0,0,1],
[1,0,0,1,1,0,1,0,1,1],
[1,0,1,1,0,1,0,1,1,1],
[0,0,1,1,0,0,1,0,1,1],
[0,0,1,0,0,1,1,1,0,0],
[1,1,1,0,1,1,1,1,0,0]]
petersen = [[0 , 1 , 0 , 0 , 1 , 1 , 0 , 0 , 0 , 0],
[0 , 1 , 0 , 0 , 0 , 1 , 0 , 0 , 0],
[0 , 1 , 0 , 0, 0 , 1 , 0 , 0],
[0 , 1, 0 , 0 , 0 , 1 , 0],
[0 , 0 , 0 , 0 , 0 , 1],
[0 , 0 , 1 , 1 , 0],
[0 , 0 , 1 , 1],
[0 , 0 , 1],
[0, 0],
[0]]
pentagonal = [[0 , 1 , 0 , 0 , 1 , 1 , 0 , 0 , 0 , 0],
[0 , 1 , 0 , 0 , 0 , 1 , 0 , 0 , 0],
[0 , 1 , 0 , 0 , 0 , 1 , 0 , 0],
[0 , 1 , 0 , 0 , 0 , 1 , 0],
[0 , 0 , 0 , 0 , 0 , 1],
[0 , 1 , 0 , 0 , 1],
[0 , 1 , 0 , 0],
[0 , 1 , 0],
[0, 1],
[0]]
M_3 = [[0, 0, 1], [0, 1], [0]]
M_4 = [[0, 1, 1, 1], [0, 0, 0], [0, 1], [0]]
M_5 = [[0, 0, 1, 1, 0], [0, 0, 0, 1], [0, 0, 1], [0, 1], [0]]
M_6 = [[0, 0, 1, 1, 0, 1], [0, 1, 1, 0, 0], [0, 1, 0, 0], [0, 0, 1], [0, 1], [0]]
M_7 = [[0, 1, 0, 0, 0, 0, 1], [0, 0, 1, 1, 0, 0], [0, 1, 1, 0, 1], [0, 1, 0, 1], [0, 0, 1], [0, 1], [0]]
M_8 = [[0, 1, 0, 1, 1, 0, 1, 0], [0, 1, 0, 1, 1, 1, 0], [0, 1, 0, 0, 0, 1], [0, 0, 0, 0, 1], [0, 0, 1, 0], [0, 1, 0], [0, 1], [0]]
M_9 = [[0, 0, 1, 1, 1, 1, 0, 1, 1], [0, 1, 1, 1, 0, 0, 0, 0], [0, 1, 0, 1, 1, 1, 0], [0, 0, 1, 0, 0, 1], [0, 1, 1, 0, 0], [0, 1, 0, 0], [0, 1, 1], [0, 0], [0]]
M_10 = [[0, 0, 0, 1, 0, 1, 0, 1, 0, 0], [0, 1, 0, 1, 1, 1, 0, 1, 0], [0, 1, 1, 0, 1, 0, 0, 0], [0, 1, 1, 0, 1, 0, 0], [0, 0, 1, 0, 0, 0], [0, 1, 1, 1, 1], [0, 0, 0, 1], [0, 0, 1], [0, 1], [0]]
M_11 = [[0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1], [0, 1, 1, 1, 0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 1, 0, 0, 1, 1], [0, 0, 1, 1, 1, 1, 0, 0], [0, 1, 0, 1, 1, 1, 1], [0, 1, 0, 1, 1, 1], [0, 1, 0, 1, 1], [0, 0, 0, 1], [0, 0, 0], [0, 1], [0]]
M_12 = [[0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0], [0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1], [0, 1, 0, 0, 0, 1, 1, 1, 1, 0], [0, 1, 0, 1, 1, 1, 0, 1, 0], [0, 0, 0, 0, 0, 0, 1, 0], [0, 0, 1, 1, 0, 0, 1], [0, 1, 0, 0, 1, 1], [0, 0, 0, 1, 1], [0, 0, 0, 1], [0, 1, 0], [0, 1], [0]]
M_13 = [[0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1], [0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1], [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0], [0, 0, 0, 1, 0, 0, 0, 0, 1, 0], [0, 1, 0, 1, 0, 1, 1, 0, 0], [0, 1, 1, 0, 1, 0, 0, 0], [0, 0, 1, 1, 0, 0, 1], [0, 1, 0, 1, 0, 0], [0, 1, 0, 1, 0], [0, 1, 0, 0], [0, 1, 0], [0, 1], [0]]
M_14 = [[0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0], [0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0], [0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1], [0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 1, 1], [0, 0, 1, 1, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0], [0, 0, 1, 0, 0, 1], [0, 0, 1, 0, 1], [0, 1, 1, 0], [0, 0, 1], [0, 1], [0]]
M_15 = [[0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 1], [0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1], [0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1], [0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0], [0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0], [0, 1, 0, 1, 0, 1, 0, 0, 1, 1], [0, 0, 0, 1, 1, 1, 1, 0, 1], [0, 0, 1, 1, 0, 0, 1, 0], [0, 0, 1, 0, 1, 0, 0], [0, 1, 1, 0, 1, 0], [0, 1, 0, 1, 1], [0, 0, 0, 0], [0, 0, 0], [0, 0], [0]]
all_grahps = [M_3, M_4, M_5, M_6, M_7, M_8, M_9, M_10, M_11, M_12] #, M_13, M_14, M_15