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kruskal_try2.py
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import numpy as np
import sys
import random
import time
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-s", action="store_true", dest="stock")
parser.add_option("-v", action="store_true", dest="verbose")
parser.add_option("-m", action="store_true", dest="matrix")
parser.add_option("-e", action="store_true", dest="edge_list")
parser.add_option("-d", action="store_true", dest="distance")
parser.add_option("-c", action="store_true", dest="clock")
parser.add_option("-f", action="store_true", dest="file")
parser.add_option("-r", "--random", action="store", type="int", dest="random", help="randomizes edge weights for the adjancency matrix")
parser.add_option("-l", "--limit", action="store", type="int", dest="random_limit", help="upper limit to the randomizer")
(options, args) = parser.parse_args()
def kruskal(n, m, E):
i = 0
j = 0
p = 0
q = 0
flag_start = True
flag_stop = False
e = (0,0)
# Sort the me edges in E by weight in nondecreasing order;
F_list = []
F_mat = []
row = []
start_index_list = []
stop_index_list = []
vert_set = set([])
vert_set_list = []
candidate = set([])
# print "F_mat = ", F_mat
# print "E = ", E
# sort E
E.sort(key=lambda tup: int(tup[2]))
# print "[sort] E = ", E
k = 0
while ( len(F_list) < (n-1)):
candidate = set( [ E[k][0], E[k][1] ] )
# print "vert_set = ", vert_set
# print "candidate = ", candidate
# find where
index_of_set = findLocationOfSet(vert_set_list, candidate)
# print "index_of_set: ", index_of_set
if index_of_set != -1:
num_of_same_verts = len(vert_set_list[index_of_set] & candidate)
else:
num_of_same_verts = 0
# print "num_of_same_verts = ", num_of_same_verts
# 2-peices of graphs
if num_of_same_verts == 0:
# fuse the set
vert_set_list.append(candidate)
# print "vert_set_list = ", vert_set_list
# append that edge
F_list.append(E[k])
# print "F_list = ", F_list
# adding on to this graph
elif num_of_same_verts == 1:
# at the correct set, unify the sets
vert_set_list[index_of_set] = vert_set_list[index_of_set].union(candidate)
# print "vert_set_list = ", vert_set_list
# append that edge
F_list.append(E[k])
# print "F_list = ", F_list
# else:
# print ""
k = k + 1
# print ""
# return the edge list and matrix
return F_list
def isPromising(vert_set, candidate):
# print "isPromising : vert_set & candidate : ", len(vert_set & candidate)
if len(vert_set & candidate) >= 2:
return False
return True
def findLocationOfSet(vert_set_list, candidate):
for i in range (0, len(vert_set_list)):
# print "vert_set_list[i] = ", vert_set_list[i]
# print "candidate = ", candidate
if len(vert_set_list[i] & candidate) >= 1:
return i
# default to NEG one for not present
return -1
def get_edge_list(mat):
n = len(mat[0])
F_list = []
inf = sys.maxint
for i in range(0, n):
for j in range(i+1, n):
edge_weight = mat[i][j]
if edge_weight < (inf - 1):
F_list.append((i, j, mat[i][j]))
return F_list
def edge_list_to_adj_matrix(edge_list):
row = []
F_mat = []
for i in range(0,n):
for j in range(0,n):
row.append(0)
F_mat.append(row)
row = []
for x in range(0,len(edge_list)):
i = edge_list[x][0]
j = edge_list[x][1]
weight = edge_list[x][2]
F_mat[i][j] = weight
return F_mat
def get_dist_upper_triange(matrix):
total = 0
for i in range(0,n):
for j in range(i,n):
total = total + matrix[i][j]
return total
def uniqueify_dble_tup( items ):
print "================================="
print ""
new_items = []
for i in range(0,len(items)):
new_items.append(items[i])
for i in range(0, len(new_items) - 1):
item1 = int(new_items[i][0])
for j in range(i+1, len(new_items)):
item2 = int(new_items[j][0])
if item1 == item2:
new_items[i] = (-(i+1),-(i+1))
new_new_items = []
for i in range (0, len(new_items)):
if new_items[i][0] > 0:
new_new_items.append(new_items[i])
print "leaving! ... new_new_items = ", str(new_new_items)
print ""
print "================================="
return new_new_items
# ==============================================================
# ============================ MAIN ============================
# ==============================================================
if __name__ == "__main__":
inf = sys.maxint
if options.random:
n = options.random
random_limit = 10
if options.random_limit:
random_limit = options.random_limit
W = []
row = []
for i in range(0,n):
for j in range(0,n):
row.append(0)
W.append(row)
row = []
for i in range(0,n):
for j in range(i+1,n):
W [i][j] = random.randint(1,random_limit)
else:
n = 5
W = [
[0,3,inf,11,inf],
[3,0,12,6,9],
[inf,12,0,4,4],
[11,6,4,0,2],
[inf,9,4,2,0]
]
if options.verbose:
print "W = \n", np.squeeze(np.asarray(W))
F_list = get_edge_list(W)
if options.verbose:
print "edge list = ", F_list
print "edge list length = ", len(get_edge_list(W))
m = len(get_edge_list(W))
if options.clock:
clock_start = time.clock()
# ======================================================
K_list = kruskal(n, m, F_list)
# ======================================================
if options.clock:
clock_stop = time.clock()
K_mat = edge_list_to_adj_matrix(K_list)
if options.verbose:
print "edge list = ", F_list
print "K_mat = \n", np.squeeze(np.asarray(K_mat))
# mirror about diagonal
for i in range(0, n):
for j in range (0, n):
K_mat[j][i] = K_mat[i][j]
print "Result"
print "============="
print "MST matrix = "
print np.squeeze(np.asarray(K_mat))
print "Edge list Length = ", get_dist_upper_triange(K_mat)
if options.verbose:
print "K_list = ", K_list
print "K_mat = \n", np.squeeze(np.asarray(K_mat))
if options.clock:
total_clock = clock_stop - clock_start
print "total_time = ", total_clock, " seconds"
# F_list, F_mat = kruskal(n)
if options.file and options.clock:
file_data = open("data_kruskals.txt", 'r+')
# sort the file
file_list = list(file_data)
file_data.close()
file_data = open("data_kruskals.txt", 'w')
file_n_val = []
file_time_val = []
split_line = []
file_tuples = []
print "file_list = ",file_list
for i in range (0, len(file_list)):
split_line = file_list[i].split(' ')
file_n_val.append(split_line[0])
file_time_val.append(split_line[1].split('\n')[0])
file_tuples.append( (split_line[0], split_line[1].split('\n')[0] ))
file_tuples.append( (str(n),total_clock))
file_tuples = uniqueify_dble_tup(file_tuples)
print "[unsort] file_tuples = ", file_tuples
file_tuples.sort(key=lambda tup: int(tup[0]))
print "[sort] file_tuples = ", file_tuples
# write out
for i in range (0, len(file_tuples)):
theLine = str(file_tuples[i][0]) + ' ' + str(file_tuples[i][1]) + '\n'
print "writing line : ", theLine
file_data.write(theLine)
print "file_n_val = ", file_n_val
print "file_time_val = ", file_time_val
print "file_tuples = ", file_tuples
file_data.close()
# theLine = str(n)+ " " + str(total_clock) + "\n"
# file_data.write( theLine )