def greed(G, iterations, cost_schedule, land, ws, greed_i):
colormap = []
score_array = []
# vraag de kleur op van een specifieke node
color = nx.get_node_attributes(G, 'color')
for node in G.nodes():
# voeg de kleur toe in de array
colormap.append(color[node])
# bereken de score
tScore = scoreCounter(G, cost_schedule)
loopA = iterations
for i in range(loopA):
G = greedy(G, colormap, cost_schedule, tScore)
tScore, Temp = scoreCounter(G, cost_schedule)
score_array.append(tScore)
print("score ", tScore)
excel_writer_greedy(score_array, land, greed_i, ws)
return G, tScore
def hillclimber(G, iterations, cost_schedule, land, hill_i):
print(hill_i)
best_G = copy.deepcopy(G)
alle_scores = []
for iter in range(iterations):
# EXPONENTIAL
T = iterations * (0.995 ** (iter * 20))
# store the old state
old_G = copy.deepcopy(G)
old_S, colormap = scoreCounter(old_G, cost_schedule)
# randomly swap a node's color
G = randomSwap(G)
# get the new score
new_S, colormap = scoreCounter(G, cost_schedule)
# keep the new state if its an improvement
if new_S < old_S:
alle_scores.append(new_S)
if new_S < beste_scores[0]:
beste_scores.append(new_S)
beste_scores.sort()
best_G = copy.deepcopy(G)
# print(new_S)
old_S = new_S
old_G = G
elif sAnneal(T, old_S, new_S) == 1:
alle_scores.append(new_S)
# print("ANEEALING DONEEEE")
old_S = new_S
old_G = G
# go back to the previous state since it's worse
else:
G = old_G
# excel_writer(alle_scores, land, ws, hill_i, iterations)
# print(beste_scores)
return best_G, old_S
def main():
# maak een random indeling
land = input("welk land wil je plotten? (RUSSIA/UKRAINE/USA) ")
nodescsv = land + "/nodes.csv"
edgescsv = land + "/edges.csv"
G = dataLoader(nodescsv, edgescsv)
G = rand(G)
cost_table = int(input("welke kosten tabel? 1 t/m 4 ")) - 1
# bereken de score
total_costs, colormap = scoreCounter(G, cost_table)
destination = land + "/hiScore.xls"
algo = input('welke algoritme? (random/greedy/hillclimber) ')
if algo == 'random':
# show de random indeling
dataWriter(G, destination, cost_table, total_costs, algo)
title = land + " Score " + str(total_costs)
nx.draw_networkx(G, with_labels=True, node_color=colormap)
plt.title(title)
plt.show()
if algo == 'greedy':
greed_nr = int(input("how many times do you want to run greedy? "))
iter = int(input("how many iterations? "))
wb = xlwt.Workbook()
ws = wb.add_sheet("Scores", cell_overwrite_ok=True)
for greed_i in range(greed_nr):
G, score = greed(G, iter, cost_table, land, ws, greed_i)
total_costs, colormap = scoreCounter(G, cost_table)
dataWriter(G, destination, cost_table, total_costs, algo)
G = rand(G)
destin = land + "/greedy_scores.xls"
wb.save(destin)
if algo == 'hillclimber':
hill_nr = int(
input("how many times do you want to run the hillclimber? "))
iter = int(input("how many iterations? "))
wb = xlwt.Workbook()
ws = wb.add_sheet("Scores", cell_overwrite_ok=True)
for hill_i in range(hill_nr):
G, score = hillclimber(G, iter, cost_table, land, ws, hill_i)
total_costs, colormap = scoreCounter(G, cost_table)
dataWriter(G, destination, cost_table, total_costs, algo)
G = rand(G)
destin = land + "/hill_climber_scores.xls"
wb.save(destin)
def hillOld(G, iterations, cost_schedule):
colormap = []
# vraag de kleur op van een specifieke node
color = nx.get_node_attributes(G, 'color')
for node in G.nodes():
# voeg de kleur toe in de array
colormap.append(color[node])
# bereken de score
tScore = scoreCounter(G, cost_schedule)
print(tScore, " score")
loopA = iterations
for i in range(loopA):
G = hillclimber(G, colormap, cost_schedule, tScore)
tScore = scoreCounter(G, cost_schedule)
print(tScore, " scoreF1")
return G, tScore
def main():
# maak een random indeling
land = "UKRAINE"
nodescsv = land + "/nodes.csv"
edgescsv = land + "/edges.csv"
G = dataLoader(nodescsv, edgescsv)
G = rand(G)
cost_table = 2
# bereken de score
total_costs, colormap = scoreCounter(G, cost_table)
destination = land + "/hiScore.xls"
algo = "greedy"
if algo == 'random':
# show de random indeling
dataWriter(G, destination, cost_table, total_costs, algo)
nx.draw_networkx(G, with_labels=True, node_color=colormap)
plt.show()
if algo == 'greedy':
iter = 5
# # draai hillclimber x aantal keer
G, score = greed(G, iter, cost_table)
total_costs, colormap = scoreCounter(G, cost_table)
dataWriter(G, destination, cost_table, total_costs, algo)
nx.draw_networkx(G, with_labels=True, node_color=colormap)
plt.show()
if algo == 'hillclimber':
iter = int(input("how many iterations? "))
G, score = hillclimber(G, iter, cost_table)
total_costs, colormap = scoreCounter(G, cost_table)
dataWriter(G, destination, cost_table, total_costs, algo)
nx.draw_networkx(G, with_labels=True, node_color=colormap)
plt.show()
from scorecalculator import scoreCounter
G = nx.Graph()
land = input("welk land wil je plotten? (RUSSIA/UKRAINE/USA) ")
destination = land + "/hiScore.xls"
edgescsv = land + "/edges.csv"
book = xlrd.open_workbook(destination)
sh = book.sheet_by_index(0)
n = 0
for rows in sh.col(0):
G.add_node(str(rows.value), color=sh.col(1)[n].value)
n += 1
G.remove_node(str(sh.col(0)[0].value))
cost_table = int(sh.col(0)[0].value - 1)
# lijnen tussen staten
with open(edgescsv, 'r') as csvfile:
plots = csv.reader(csvfile, delimiter=',')
for row in plots:
G.add_edge(str(row[0]), str(row[1]))
# lees de oude score uit file
total_costs, colormap = scoreCounter(G, cost_table)
title = land + " Score " + str(total_costs)
nx.draw_networkx(G, with_labels=True, node_color=colormap)
plt.title(title)
plt.show()