def test_delete_between(self):
even = range(0, 20, 2)
odd = range(1, 20, 2)
numbers = even + odd
numbers.sort()
sl = SkipList.SkipList()
for number in numbers:
sl.insert(number)
for number in odd:
sl.delete(number)
self.assertEqual(even, sl.skip_list_as_list())
def test_skip_list():
skip_list = SkipList.SkipList()
i = 0
for i in range(10):
skip_list.insert(i)
i += 1
skip_list.print_list()
skip_list.print_nice()
print
for i in range(10):
skip_list.delete(i)
skip_list.print_nice()
print
def compare_insertion_and_search():
rounds = int(raw_input('How many rounds of test? '))
insertions = int(
raw_input('How many insertions (nodes in the structure)? '))
top_percent = float(
raw_input('How many percent of the values are searched? '))
repeat = int(raw_input('How many times those values are searched? '))
values = random.sample(range(insertions * 10), insertions)
search_values = random.sample(values, int(top_percent * insertions / 100))
searches = search_values * repeat
random.shuffle(searches)
for round in range(rounds):
print '-' * 20
sl = SkipList.SkipList()
st = SplayTree.SplayTree()
t = Treap.Treap()
structures = [(sl, 'Skip list'), (st, 'Splay tree'), (t, 'Treap')]
print '\nInsertions:'
for structure in structures:
time_begin = time.time()
for key in range(insertions):
structure[0].insert(key)
print('Inserting ' + str(insertions) + ' values to empty ' +
structure[1] + ' took ' + str(time.time() - time_begin) +
' seconds')
print '\nSearches:'
time_begin = time.time()
for key in searches:
sl.search(key)
print('Searching ' + str(len(searches)) +
' values from skip list took ' + str(time.time() - time_begin) +
' seconds')
time_begin = time.time()
for key in searches:
st.search(st.root, key)
print('Searching ' + str(len(searches)) +
' values from splay tree took ' + str(time.time() - time_begin) +
' seconds')
time_begin = time.time()
for key in searches:
t.search(t.root, key)
print('Searching ' + str(len(searches)) + ' values from treap took ' +
str(time.time() - time_begin) + ' seconds')
def main():
# if the user sent specified 1 thing for the commandline
if (len(sys.argv) == 2):
# try to convert the thing to a positve number.
try:
count = int(sys.argv[1])
if count < 0:
sys.exit(0)
except:
print("Please enter in a positive whole number")
sys.exit(0)
#!!!Ziptree Test!!!
start_time = time.time()
ziptree = ZipTree(None)
for i in range(count):
temp = node(random.randint(0, count), None, None)
ziptree.insert(temp)
print("--- %s bytes --- ZipTree" % ziptree.getTreeSize())
for i in range(count):
temp = ziptree.find(i)
while (temp is not None):
ziptree.delete(temp)
temp = ziptree.find(i)
print("--- %s seconds --- ZipTree" % (time.time() - start_time))
#!!!Skiplist Test!!!
start_time = time.time()
skiplist = SkipList(count, 0.5)
for i in range(count):
skiplist.insertElement(random.randint(0, count))
print("--- %s bytes --- SkipList" % skiplist.getListSize())
for i in range(count):
while (skiplist.searchElement(i) is True):
skiplist.deleteElement(i)
print("--- %s seconds --- SkipList" % (time.time() - start_time))
#!!!Treap Test!!!
start_time = time.time()
treap = Treap()
for i in range(count):
treap.insert(random.randint(0, count))
print("--- %s bytes --- Treap" % treap.getTreeSize())
for i in range(count):
while (treap.find(i) is not None):
treap.delete(i)
print("--- %s seconds --- Treap" % (time.time() - start_time))
else:
print("This program takes in 1 postive integer value.")
# import random2 as r2 # learn more: https://python.org/pypi/random2 from SkipList import * # print(r2.random()) s1 = SkipList() n1 = NodoSkip(1) s1.getCabeza() # s1.inserta(n1) # s1.print()
def test_search_succesful(self):
sl = SkipList.SkipList()
for number in range(100):
sl.insert(number)
for number in [0, 11, 17, 27, 99, 50, 11, 17]:
self.assertTrue(sl.search(number) == number)
def test_search_unsuccesful(self):
sl = SkipList.SkipList()
sl.insert(1)
self.assertIsNone(sl.search(2))
def test_skip_list_as_list(self):
sl = SkipList.SkipList()
for key in range(10):
sl.insert(key)
self.assertEqual(range(10), sl.skip_list_as_list())
### Example ###
from SkipList import *
## Insert Keys
# Create a Skip List with N set to the
# desired number of elements to be stored
a = SkipList(20)
lis = list(range(20, 0,-1))
for key in lis:
a.insert(key)
a.displayList()
## Check if a key is present
print ("\nDoes the list contain 3?", a.contains(3))
## Remove a key
a.remove(3)
a.displayList()
print ("\nDoes the list contain 3?", a.contains(3))
## Return the length of the skip list
print ("\nThe length of the skip list is :", len(a))
from SkipList import * sk = SkipList([3, 2, 23, 4, 2, -1, 4, 5, -13]) print(sk) sk.erase(4) print(sk)
def main(elements, adjust, exp):
'''
Principal
'''
insertions = elements
searches = int(0.5*elements)
not_found_searches = int(0.25*searches)
swaps_amount = int(0.05*elements) # aumentando la cantidad de swaps de cada iteracion
init = False
analizer = ExperimentAnalyzer(exp)
print('n :' + str(elements))
print('experiments: ' + str(exp))
for e in range(exp):
sequence = RandomSequence(elements, 10**5)
while (not init) or abb_comps - abbr_comps > abbr_comps*adjust:
if not init:
mean_height = 0
iteration = 0
init = True
# Número de iteracion para acercar comportamiento de árboles
iteration += 1
# print('.'),
sys.stdout.flush()
# Se definen las estructuras
abb_tree = ABB()
abbr_tree = ABBRandom()
skip_list = SkipList()
# Contadores
abb_comps = 0
abbr_comps = 0
skip_comps = 0
abb_search_comps = 0
abbr_search_comps = 0
skip_search_comps = 0
# Lista para ABB
abb_elements = sequence.k_swaps(swaps_amount)
# Inserciones
for i in range(insertions):
abb_comps += abb_tree.insert(abb_elements[i])
abbr_comps += abbr_tree.insert(sequence.get_element(i))
skip_comps += skip_list.insert(sequence.get_element(i))
# Busquedas
for i in range(searches):
if i < not_found_searches:
elem = sequence.get_random_free_element()
else:
elem = sequence.get_random_element()
abb_search_comps += abb_tree.search(elem)[1]
abbr_search_comps += abbr_tree.search(elem)[1]
skip_search_comps += skip_list.search(elem)[1]
# Altura de skip list
mean_height += 1.0*skip_list.max_height
# Siguiente iteración
sequence.elements = abb_elements
# print(str(1.0*abb_comps/insertions) + ' ' + str(1.0*abbr_comps/insertions) + ' ' + str(1.0*skip_comps/insertions))
# Suma de resultados promedio (n operaciones)
# Resultados: Inserciones
abb_comps = 1.0*abb_comps/insertions
abbr_comps = 1.0*abbr_comps/insertions
skip_comps = 1.0*skip_comps/insertions
# Resultados: Busquedas
abb_search_comps = 1.0*abb_search_comps/searches
abbr_search_comps = 1.0*abbr_search_comps/searches
skip_search_comps = 1.0*skip_search_comps/searches
# Resultados: Altura de Skip List
mean_height = 1.0*mean_height/iteration
print('\ninsertions: ' + str(abb_comps) + ',' + str(abbr_comps) + ',' + str(skip_comps))
print('searches: ' + str(abb_search_comps) + ',' + str(abbr_search_comps) + ',' + str(skip_search_comps))
print('skiplist height: ' + str(mean_height))
print('total swaps: ' + str(swaps_amount*iteration))
analizer.add_abb_result(abb_comps, abb_search_comps, swaps_amount*iteration)
analizer.add_abbr_result(abbr_comps, abbr_search_comps)
analizer.add_skip_list_result(skip_comps, skip_search_comps, mean_height)
init = False
print('\n')
analizer.compute_errors()
analizer.show_results()
print('\n')
def main(elements, exp):
'''
Principal
'''
insertions = elements
searches = int(0.5*elements)
not_found_searches = int(0.25*searches)
analizer = ExperimentAnalyzer(exp)
print('n :' + str(elements))
print('experiments: ' + str(exp))
for e in range(exp):
sequence = RandomSequence(elements, 10**5)
swaps_amount = int(0.7*elements) # swaps
# Contadores
abb_comps = 0
abbr_comps = 0
skip_comps = 0
abb_search_comps = 0
abbr_search_comps = 0
skip_search_comps = 0
# Se definen las estructuras
abb_tree = ABB()
abbr_tree = ABBRandom()
skip_list = SkipList()
# Lista para ABB
abb_elements = sequence.k_swaps(swaps_amount)
# Inserciones
for i in range(insertions):
abb_comps += abb_tree.insert(abb_elements[i])
abbr_comps += abbr_tree.insert(abb_elements[i])
skip_comps += skip_list.insert(abb_elements[i])
# Busquedas
for i in range(searches):
if i < not_found_searches:
elem = sequence.get_random_free_element()
else:
elem = sequence.get_random_element()
abb_search_comps += abb_tree.search(elem)[1]
abbr_search_comps += abbr_tree.search(elem)[1]
skip_search_comps += skip_list.search(elem)[1]
# Altura de skip list
mean_height = 1.0*skip_list.max_height
# Suma de resultados promedio (n operaciones)
# Resultados: Inserciones
abb_comps = 1.0*abb_comps/insertions
abbr_comps = 1.0*abbr_comps/insertions
skip_comps = 1.0*skip_comps/insertions
# Resultados: Busquedas
abb_search_comps = 1.0*abb_search_comps/searches
abbr_search_comps = 1.0*abbr_search_comps/searches
skip_search_comps = 1.0*skip_search_comps/searches
print('\ninsertions: ' + str(abb_comps) + ',' + str(abbr_comps) + ',' + str(skip_comps))
print('searches: ' + str(abb_search_comps) + ',' + str(abbr_search_comps) + ',' + str(skip_search_comps))
print('skiplist height: ' + str(mean_height))
print('total swaps: ' + str(swaps_amount))
analizer.add_abb_result(abb_comps, abb_search_comps, swaps_amount)
analizer.add_abbr_result(abbr_comps, abbr_search_comps)
analizer.add_skip_list_result(skip_comps, skip_search_comps, mean_height)
analizer.compute_errors()
analizer.show_results()
print('\n')
