def maximize_pairwise_exchange(cycles, vertices, dirname, edges, ilp):
"""[summary]
Args:
cycles ([type]): [description]
vertices ([type]): [description]
dirname ([type]): [description]
edges ([type]): [description]
ilp ([type]): [description]
Returns:
[type]: [description]
"""
coef = []
precomputation = CyclePrecomputation()
for cycle in cycles:
x = precomputation.calculate_backarc(cycle, edges) # + len(cycle)
x = x + len(cycle)
print(cycle, " ", x, " ", len(cycle), " ", x - len(cycle))
coef.append(x)
solution_values = optimize_length(cycles, vertices, dirname, coef, ilp)
print(solution_values)
return solution_values
def run_results(solution_values, cycles, altruistic, edges, cycleswt):
transplants = 0
altruistic_involved = 0
paired_transplants = 0
two_ways = 0
three_ways = 0
three_ways_embedded = 0
effective_pairwise = 0
weight = 0
precomputation = CyclePrecomputation()
for i in range(0, len(solution_values)):
if solution_values[i] != 0:
transplants = transplants + len(cycles[i])
if cycles[i][0] == cycles[i][-1]:
transplants = transplants - 1
paired_transplants = paired_transplants + len(cycles[i]) - 1
if len(cycles[i]) == 3:
two_ways = two_ways + 1
effective_pairwise = effective_pairwise + 1
elif len(cycles[i]) == 4:
three_ways = three_ways + 1
effective_pairwise = effective_pairwise + len(
cycles[i]) - 1
three_ways_embedded = (
three_ways_embedded +
precomputation.calculate_backarc(cycles[i], edges))
else:
effective_pairwise = effective_pairwise + len(
cycles[i]) - 1
else:
altruistic_involved = altruistic_involved + 1
weight = weight + cycleswt[tuple(cycles[i])]
return (
transplants + len(altruistic) - altruistic_involved,
paired_transplants,
len(altruistic) - altruistic_involved,
two_ways,
three_ways,
three_ways_embedded,
effective_pairwise,
weight,
)
def maximize_pairwise_exchange(cycles, vertices, dirname, edges, ilp):
coef = []
precomputation = CyclePrecomputation()
for cycle in cycles:
x = precomputation.calculate_backarc(cycle, edges) #+ len(cycle)
x = x + len(cycle)
print(cycle, " ", x, " ", len(cycle), " ", x - len(cycle))
coef.append(x)
solution_values = optimize_length(cycles, vertices, dirname, coef, ilp)
print(solution_values)
return solution_values
def pipeline(file_name, option, max_cycle_length, max_chain_length, ilp):
# x = datetime.datetime.now()
x = "result"
path = os.getcwd() + "/"
dirName = path + str(x)
# if not os.path.exists(dirName):
# os.mkdir(dirName)
# else:
# print("Directory " , dirName , " already exists")
# sys.exit(-1)
# delete the directory if exists
if os.path.exists(dirName):
shutil.rmtree(dirName)
# create an empty directory
os.mkdir(dirName)
destination = dirName
shutil.copy(file_name, destination)
graph = dirName + "/" + "graph"
f = open(graph, "w")
json_convert = DataConvert(json_file)
precomputation = CyclePrecomputation()
names, edges, weight, altruistic_donors = json_convert.convert_altruistic()
f.write(str(len(names)) + " " + str(len(altruistic_donors)) + " " + str(len(edges)))
for name in names:
f.write(str(name) + "\n")
for altruistic_donor in altruistic_donors:
f.write(str(altruistic_donor) + "\n")
for edge in edges:
f.write("[" + edge[0] + " " + edge[1] + "] " + str(weight[tuple(edge)]) + "\n")
f.close()
# option = int(input("Choose option \n1.Maximize the number of effective pairwise exchange \n2.Maximize the total number of transplants\n3.Maximize the total number of backarcs\n4.Maximize the total weight\n5.Minimize the number of 3-way exchange\n6.Maximize the number of pairwise exchange "))
# Basically maximizing the total number of cycles which does not involve altruistic donor
start = time.time()
if option == 1:
cyclesAndChains = precomputation.findCyclesAndChains(
names, max_cycle_length, max_chain_length, altruistic_donors, edges
)
end = time.time()
print(cyclesAndChains)
cycleandchain_wt = precomputation.findwt(cyclesAndChains, weight)
solution_values = maximize_pairwise_exchange(
cyclesAndChains, names, dirName, edges, ilp
)
transplants = print_solution(
1,
"Maximize the number of effective pairwise exchange",
max_cycle_length,
solution_values,
cyclesAndChains,
altruistic_donors,
edges,
cycleandchain_wt,
names,
dirName,
)
fillexcel(
len(names),
len(altruistic_donors),
max_cycle_length,
max_chain_length,
transplants,
"Maximize the number of effective pairwise exchange",
)
# Maximize the number of patients that get a kidney. This will involve altruistic donors as well
elif option == 2:
cyclesAndChains = precomputation.findCyclesAndChains(
names, max_cycle_length, max_chain_length, altruistic_donors, edges
)
end = time.time()
cycleandchain_wt = precomputation.findwt(cyclesAndChains, weight)
solution_values = maximize_total_transplants(
cyclesAndChains, names + altruistic_donors, dirName, ilp
)
transplants = print_solution(
1,
"Maximize the total number of transplants",
max_cycle_length,
solution_values,
cyclesAndChains,
altruistic_donors,
edges,
cycleandchain_wt,
names,
dirName,
)
fillexcel(
len(names),
len(altruistic_donors),
max_cycle_length,
max_chain_length,
transplants,
"Maximize the total number of transplants",
)
# No of backarcs in 3-way exchange should be maximized(a 3-way exchange can contain more than one backarc.)
elif option == 3:
print("Yet to be done")
sys.exit()
# Maximize the total weight calculated by summing over all cycles and chains
elif option == 4:
cyclesAndChains = precomputation.findCyclesAndChains(
names, max_cycle_length, max_chain_length, altruistic_donors, edges
)
end = time.time()
cycleandchain_wt = precomputation.findwt(cyclesAndChains, weight)
solution_values = maximize_total_weight(
cyclesAndChains, names + altruistic_donors, cycleandchain_wt, dirName, ilp
)
transplants = print_solution(
1,
"Maximize the total weight",
max_cycle_length,
solution_values,
cyclesAndChains,
altruistic_donors,
edges,
cycleandchain_wt,
names,
dirName,
)
fillexcel(
len(names),
len(altruistic_donors),
max_cycle_length,
max_chain_length,
transplants,
"Maximize the total weight",
)
elif option == 5:
print("Yet to be done")
sys.exit()
# Maximize the number of pairwise exchange plus unused altruists:-
elif option == 6:
cyclesAndChains = precomputation.findCyclesAndChains(
names, 2, 1, altruistic_donors, edges
)
end = time.time()
cycleandchain_wt = precomputation.findwt(cyclesAndChains, weight)
solution_values = maximize_total_transplants(
cyclesAndChains, names + altruistic_donors, dirName, ilp
)
transplants = print_solution(
1,
"Maximize pairwise exchange",
2,
solution_values,
cyclesAndChains,
altruistic_donors,
edges,
cycleandchain_wt,
names,
dirName,
)
fillexcel(
len(names),
len(altruistic_donors),
max_cycle_length,
max_chain_length,
transplants,
"Maximize the number of pairwise exchange",
)
print("Runtime of the program is ", end - start)
def run_results(solution_values, cycles, altruistic, edges, cycleswt):
"""[summary]
Args:
solution_values ([type]): [description]
cycles ([type]): [description]
altruistic ([type]): [description]
edges ([type]): [description]
cycleswt ([type]): [description]
Returns:
[type]: [description]
"""
transplants = 0
altruistic_involved = 0
paired_transplants = 0
two_ways = 0
three_ways = 0
three_ways_embedded = 0
effective_pairwise = 0
weight = 0
precomputation = CyclePrecomputation()
for i in range(len(solution_values)):
if solution_values[i] != 0:
transplants += len(cycles[i])
if cycles[i][0] == cycles[i][-1]:
transplants -= 1
paired_transplants = paired_transplants + len(cycles[i]) - 1
if len(cycles[i]) == 3:
two_ways += 1
effective_pairwise += 1
elif len(cycles[i]) == 4:
three_ways += 1
effective_pairwise = effective_pairwise + len(
cycles[i]) - 1
three_ways_embedded += precomputation.calculate_backarc(
cycles[i], edges)
else:
effective_pairwise = effective_pairwise + len(
cycles[i]) - 1
else:
altruistic_involved += 1
weight += cycleswt[tuple(cycles[i])]
return (
transplants + len(altruistic) - altruistic_involved,
paired_transplants,
len(altruistic) - altruistic_involved,
two_ways,
three_ways,
three_ways_embedded,
effective_pairwise,
weight,
)
def pipeline(n):
# with open('kidney.csv', 'a', newline='') as file:
# writer = csv.DictWriter(file, fieldnames=fnames)
# writer.writeheader()
if len(sys.argv) != 2:
print("Error :Please specify number of nodes")
sys.exit(-1)
file_name = sys.argv[1]
x = datetime.datetime.now()
dirName = str(x)
if not os.path.exists(dirName):
os.mkdir(dirName)
else:
print("Directory ", dirName, " already exists")
sys.exit(-1)
destination = dirName
shutil.copy(file_name, destination)
graph = dirName + '/' + "graph"
f = open(graph, "w")
json_convert = DataConvert()
precomputation = CyclePrecomputation()
names, edges, weight, altruistic_donors = json_convert.convert_altruistic(
file_name)
f.write(
str(len(names)) + " " + str(len(altruistic_donors)) + " " +
str(len(edges)))
for name in names:
f.write(str(name) + "\n")
for altruistic_donor in altruistic_donors:
f.write(str(altruistic_donor) + "\n")
for edge in edges:
f.write("[" + edge[0] + " " + edge[1] + "] " +
str(weight[tuple(edge)]) + "\n")
f.close()
max_cycle_length = int(input("Maximum Cycle size"))
max_chain_length = int(input("Altruistic Chain Length"))
option = int(
input(
"Choose option \n1.Maximize the number of effective pairwise exchange \n2.Maximize the total number of transplants\n3.Maximize the total number of backarcs\n4.Maximize the total weight\n5.Minimize the number of 3-way exchange\n6.Maximize the number of pairwise exchange"
))
#Basically maximizing the total number of cycles which does not involve altruistic donor
start = time.time()
if option == 1:
cyclesAndChains = precomputation.findCyclesAndChains(
names, max_cycle_length, max_chain_length, altruistic_donors,
edges)
end = time.time()
print(cyclesAndChains)
cycleandchain_wt = precomputation.findwt(cyclesAndChains, weight)
solution_values = maximize_pairwise_exchange(cyclesAndChains, names,
dirName, edges)
transplants = print_solution(
1, "Maximize the number of effective pairwise exchange",
max_cycle_length, solution_values, cyclesAndChains,
altruistic_donors, edges, cycleandchain_wt, names, dirName)
fillexcel(len(names), len(altruistic_donors), max_cycle_length,
max_chain_length, transplants,
"Maximize the number of effective pairwise exchange")
#Maximize the number of patients that get a kidney. This will involve altruistic donors as well
if option == 2:
cyclesAndChains = precomputation.findCyclesAndChains(
names, max_cycle_length, max_chain_length, altruistic_donors,
edges)
end = time.time()
cycleandchain_wt = precomputation.findwt(cyclesAndChains, weight)
solution_values = maximize_total_transplants(cyclesAndChains,
names + altruistic_donors,
dirName)
transplants = print_solution(
1, "Maximize the total number of transplants", max_cycle_length,
solution_values, cyclesAndChains, altruistic_donors, edges,
cycleandchain_wt, names, dirName)
fillexcel(len(names), len(altruistic_donors), max_cycle_length,
max_chain_length, transplants,
"Maximize the total number of transplants")
#No of backarcs in 3-way exchange should be maximized(a 3-way exchange can contain more than one backarc.)
if option == 3:
print("Yet to be done")
#Maximize the total weight calculated by summing over all cycles and chains
if option == 4:
cyclesAndChains = precomputation.findCyclesAndChains(
names, max_cycle_length, max_chain_length, altruistic_donors,
edges)
end = time.time()
cycleandchain_wt = precomputation.findwt(cyclesAndChains, weight)
solution_values = maximize_total_weight(cyclesAndChains,
names + altruistic_donors,
cycleandchain_wt, dirName)
transplants = print_solution(1, "Maximize the total weight",
max_cycle_length, solution_values,
cyclesAndChains, altruistic_donors, edges,
cycleandchain_wt, names, dirName)
fillexcel(len(names), len(altruistic_donors), max_cycle_length,
max_chain_length, transplants, "Maximize the total weight")
if option == 5:
print("Yet to be done")
#Maximize the number of pairwise exchange plus unused altruists:-
if option == 6:
cyclesAndChains = precomputation.findCyclesAndChains(
names, 2, 1, altruistic_donors, edges)
end = time.time()
cycleandchain_wt = precomputation.findwt(cyclesAndChains, weight)
solution_values = maximize_total_transplants(cyclesAndChains,
names + altruistic_donors,
dirName)
transplants = print_solution(1, "Maximize pairwise exchange", 2,
solution_values, cyclesAndChains,
altruistic_donors, edges,
cycleandchain_wt, names, dirName)
fillexcel(len(names), len(altruistic_donors), max_cycle_length,
max_chain_length, transplants,
"Maximize the number of pairwise exchange")
print("Runtime of the program is ", end - start)