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import numpy as np | ||
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def constByCost(instance): | ||
descoberto = True | ||
v_cobertura = np.zeros(instance.num_lin, dtype=np.int64) | ||
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v_sol = np.zeros(instance.num_col, dtype=np.int64) | ||
cost_sol = 0 | ||
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# Sort indices by the cost (equivalent of sortperm in Julia) | ||
v_ind = np.argsort(instance.v_cost) | ||
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j = 0 | ||
while descoberto: | ||
coluna = v_ind[j] | ||
v_sol[coluna] = 1 | ||
cost_sol += instance.v_cost[coluna] | ||
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descoberto = False | ||
for linha in range(instance.num_lin): | ||
v_cobertura[linha] += instance.m_coverage[linha][coluna] | ||
if v_cobertura[linha] == 0: | ||
descoberto = True | ||
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j += 1 | ||
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return v_sol, cost_sol, v_cobertura | ||
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def outroConst(instance): | ||
print("Implemente outro metodo construtivo") | ||
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def randomConst(instance, chrms): | ||
v_cobertura = np.zeros(instance.num_lin, dtype=np.int64) | ||
v_sol = np.zeros(instance.num_col, dtype=np.int64) | ||
cost_sol = 0 | ||
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# Sort columns by their corresponding values in the chrms (random keys vector) | ||
v_ind = np.argsort(chrms) | ||
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j = 0 | ||
descoberto = True | ||
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while descoberto: | ||
coluna = v_ind[j] # Select the column based on sorted random keys | ||
v_sol[coluna] = 1 # Mark the column as selected | ||
cost_sol += instance.v_cost[coluna] # Add the cost of the selected column | ||
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descoberto = False | ||
for linha in range(instance.num_lin): | ||
v_cobertura[linha] += instance.m_coverage[linha][coluna] | ||
if v_cobertura[linha] == 0: | ||
descoberto = True # If any row is still uncovered, continue selecting | ||
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j += 1 | ||
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return v_sol, cost_sol, v_cobertura |
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import time | ||
import random | ||
import datetime | ||
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# Include necessary files (you can import relevant functions/modules) | ||
from scp_instance import scpInstance | ||
from construtivos import constByCost, outroConst, randomConst | ||
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######################################## | ||
# Leitura dos argumentos e da instancia | ||
######################################## | ||
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# Check if the correct number of arguments are passed | ||
# ARGS in Julia refers to command-line arguments. In Python, use sys.argv. | ||
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instance_file = "Tarefa 2/data/IGC1.txt" # instance_file receives the name of the instance file | ||
cod_metodo = 2 # Method code | ||
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instance = scpInstance(instance_file) # Load instance data | ||
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######################################## | ||
# Chamada do metodo construtivo | ||
######################################## | ||
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start_time = time.time() # Start time counter | ||
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if cod_metodo == 0: | ||
S, cost, v_cobertura = constByCost(instance) # Call constByCost method | ||
elif cod_metodo == 1: | ||
S, cost, v_cobertura = outroConst(instance) # Call outroConst method | ||
else: | ||
seed = random.getrandbits(64) # Generate a random seed | ||
random.seed(seed) # Set the random seed | ||
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# Write the seed to a text file | ||
seed_file = "seed_{}.txt".format(datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S")) | ||
with open(seed_file, "w") as file: | ||
file.write(str(seed)) | ||
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chrms = [random.random() for _ in range(instance.num_col)] # Generate random keys vector | ||
S, cost, v_cobertura = randomConst(instance, chrms) # Call random method | ||
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# Calculate total time | ||
total_time = round(time.time() - start_time, 2) | ||
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# Print results | ||
print(f"Tempo: {total_time}") | ||
print(f"Custo: {cost}") | ||
print(f"Solucao: {S}") |
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class scpInstance: | ||
def __init__(self, filename: str): | ||
with open(filename, 'r') as f: | ||
s = f.read() | ||
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values = s.split() | ||
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v = 0 # iterator for values | ||
self.num_lin = int(values[v]) | ||
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v += 1 # v=1 | ||
self.num_col = int(values[v]) | ||
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v += 1 # v=2 | ||
self.v_cost = [int(values[v + j]) for j in range(self.num_col)] | ||
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v += self.num_col # v = num_col + 2 | ||
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self.m_coverage = [[0] * self.num_col for _ in range(self.num_lin)] | ||
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for i in range(self.num_lin): | ||
v += 1 | ||
cl = int(values[v]) | ||
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for _ in range(cl): | ||
v += 1 | ||
j = int(values[v]) - 1 # adjust for 0-indexing in Python | ||
self.m_coverage[i][j] = 1 |
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Cost | ||
5308,11.55 | ||
5144,9.53 | ||
4468,9.62 | ||
4782,9.41 | ||
5338,10.09 | ||
4841,9.6 | ||
5726,10.29 | ||
5180,9.84 | ||
4682,9.59 | ||
5929,10.04 | ||
Média dos custos: 5139.8 | ||
Média dos tempos: 9.956 | ||
Menor custo: 4468 |
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Cost | ||
4734,10.34 | ||
4717,9.77 | ||
5298,10.21 | ||
4531,9.99 | ||
5204,10.25 | ||
5759,10.04 | ||
4884,10.16 | ||
5025,9.89 | ||
5135,10.91 | ||
4979,10.49 | ||
Média dos custos: 5026.6 | ||
Média dos tempos: 10.205 | ||
Menor custo: 4531 |
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Cost | ||
5003,15.73 | ||
4915,17.2 | ||
4409,15.94 | ||
5470,15.98 | ||
4970,15.98 | ||
5263,14.94 | ||
4849,14.79 | ||
4747,15.68 | ||
5098,16.04 | ||
5345,15.43 | ||
Média dos custos: 5006.9 | ||
Média dos tempos: 15.771 | ||
Menor custo: 4409 |
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Cost | ||
5133,15.6 | ||
5488,15.97 | ||
5016,16.15 | ||
5109,15.54 | ||
5333,15.21 | ||
4996,15.56 | ||
5636,15.22 | ||
5135,15.37 | ||
4805,15.77 | ||
5136,15.97 | ||
Média dos custos: 5178.7 | ||
Média dos tempos: 15.636000000000001 | ||
Menor custo: 4805 |
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Cost | ||
3267,8.19 | ||
2149,7.81 | ||
2815,8.19 | ||
2809,8.0 | ||
2948,7.85 | ||
2724,7.69 | ||
3185,8.13 | ||
2564,8.11 | ||
3404,8.9 | ||
2917,7.92 | ||
Média dos custos: 2878.2 | ||
Média dos tempos: 8.079 | ||
Menor custo: 2149 |
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17849601288476634649 |
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1002435381292223730 |
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16070948480802929411 |
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8024425746243728464 |
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13857812545251570568 |
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2013193365147955844 |
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