def test_for_add_and_get_size(self):
p = PriorityQueue()
p.add(999)
p.add(222)
p.add(33)
p.add(33)
self.assertTrue(p.size(), 5)
def prim(G,start):
pq = PriorityQueue()
inf = float("infinity")
for i in G.get_vertices():
v = G.get_vertex(i)
v.set_distance(inf)
v.set_previous(None)
s = G.get_vertex(start)
s.set_distance(0)
for v in G:
pq.add(v.get_distance(), v.get_vertex_ID())
MST = []
while not pq.empty():
t = pq.extract_min()
currentVert = G.get_vertex(t[1])
MST.append((currentVert.get_previous(), currentVert.get_vertex_ID()))
for nextVert in currentVert.get_connections():
newCost = currentVert.get_weight(nextVert) + currentVert.get_distance()
if nextVert in pq and newCost<nextVert.get_distance():
nextVert.set_previous(currentVert)
nextVert.set_distance(newCost)
pq.replace_key(nextVert,newCost)
print MST
def dijkstra(G, s):
#create a priority queue
pq = PriorityQueue()
#set distance for all other vertices to "infinity"
inf = float("infinity")
for i in G.get_vertices():
v = G.get_vertex(i)
v.set_distance(inf)
#set distance of source to zero
source = G.get_vertex(s)
source.set_distance(0)
#insert all vertices into the priority queue (distance is priority)
for v in G:
pq.add(v.get_distance(), v.id)
#loop while priority queue is not empty
while not(pq.empty()):
#remove vertex with smallest distance from priority queue
t = pq.extract_min()
v = G.get_vertex(t[1])
#for each vertex w adjacent to v
for w in v.get_connections():
if w.get_distance() > (v.get_distance() + v.get_weight(w)):
w.set_previous(v)
w.set_distance(v.get_distance() + v.get_weight(w))
#loop over all nodes and print their distances
for v in G:
print "Node", v.get_vertex_ID(), "with distance", v.get_distance()
def queue_dict(dict):
term_queue = PriorityQueue()
for t in dict:
this_q_item = Q_item(t, dict[t])
term_queue.add(this_q_item)
return term_queue
def queue_dict(dict):
term_queue = PriorityQueue()
for t in dict:
this_q_item = Q_item(t, dict[t])
term_queue.add(this_q_item)
return term_queue
def sf_compression(file_name):
# open file to be read
file = open(file_name, "r")
text = file.read()
file.close()
#check for empty text file
if text == "":
print("Error: Empty Text")
else:
letter_dict = {text[0]: 1}
# place each letter into dictionary and count each letter
for x in range(1, len(text)):
if text[x] in letter_dict:
letter_dict[text[x]] = letter_dict[text[x]] + 1
else:
letter_dict[text[x]] = 1
priorityq = PriorityQueue()
# insert everything into priority queue
for x in letter_dict:
priorityq.add([x, letter_dict[x], ""])
# generate shannon-fano code
split_equal_list(priorityq, letter_dict)
print(letter_dict)
# create compressed version in text format
file = open(file_name[0:-4] + "_SFcompressed.txt", "w")
result = ""
for x in text:
result = result + letter_dict[x]
file.write(letter_dict[x])
file.close()
# create compressed version in bin format
file = open(file_name[0:-4] + "_SFcompressed.bin", "wb")
file.write(_to_Bytes(result))
file.close()
# create compression data(bitcount dictionary) in text format
file = open(file_name[0:-4] + "_SFcode.txt", "w")
file.write(str(len(result)))
file.write(str(letter_dict))
file.close()
print(result)
def sift_down_test(self):
p = PriorityQueue()
p.add(999)
p.add(222)
p.add(33)
p.add(33)
self.assertTrue(p.sift_down, 3)
p.add(45)
self.assertTrue(p.sift_down, 2)
p.add(22)
def test_for_priority_removal(self):
p = PriorityQueue()
p.add(10)
p.add(20)
p.add(1)
p.add(30)
p.add(5)
self.assertTrue(p.peek(), 1)
p.remove()
self.assertTrue(p.peek(), 5)
p.remove()
self.assertTrue(p.peek(), 10)
def priority_queue_test():
priority_queue = PriorityQueue()
priority_queue.add(1)
priority_queue.add(8)
priority_queue.add(5)
priority_queue.add(3)
priority_queue.add(4)
priority_queue.add(2)
priority_queue.add(6)
priority_queue.add(7)
priority_queue.add(0)
i = 0
# this effectively tests heap sort as well...
while not priority_queue.is_empty():
number_polled = priority_queue.poll()
assert (
number_polled == i
), "Expected %s got %s from priority queue" % (i, number_polled)
i = i + 1
def test_we_can_add_five_elements(self):
p = PriorityQueue()
p.add(10)
p.add(20)
p.add(30)
p.add(40)
p.add(50)
self.assertTrue(p.size(), 5)
self.assertTrue(p.peek(), 10)
def split_equal_list(priorityq, letter_dict):
# check if more than 1 node in priority queue
if len(priorityq.return_all()) > 1:
priorityq1 = PriorityQueue()
priorityq2 = PriorityQueue()
# add code '0' for priority queue 1
temp1 = priorityq.pop()
temp1[2] += "0"
priorityq1.add(temp1)
count0 = temp1[1]
# add code '1' for priority queue 2
temp1 = priorityq.pop()
temp1[2] += "1"
priorityq2.add(temp1)
count1 = temp1[1]
# place all nodes from priorityq into correct place
while not priorityq.empty():
temp1 = priorityq.pop()
# compare where to place next node
if count0 + temp1[1] - count1 < count1 + temp1[1] - count0:
temp1[2] += "0"
priorityq1.add(temp1)
count0 += temp1[1]
else:
temp1[2] += "1"
priorityq2.add(temp1)
count1 += temp1[1]
# call itself until base case is reached
return [
split_equal_list(priorityq1, letter_dict),
split_equal_list(priorityq2, letter_dict)
]
# base case
else:
# save code into dictionary
letter_dict[priorityq.return_all()[0]
[0]] = priorityq.return_all()[0][2]
return priorityq.return_all()
def q_test():
alan = Q_item('alan', 3)
brad = Q_item('brad', 2)
carl = Q_item('carl', 1)
alanbrad = alan + brad
tesco = PriorityQueue()
tesco.add(brad)
tesco.add(alan)
tesco.add(carl)
tesco.add(alanbrad)
print tesco
return 'q_test done'
def q_test():
alan = Q_item('alan', 3)
brad = Q_item('brad', 2)
carl = Q_item('carl', 1)
alanbrad = alan + brad
tesco = PriorityQueue()
tesco.add(brad)
tesco.add(alan)
tesco.add(carl)
tesco.add(alanbrad)
print tesco
return 'q_test done'
