def test_find_last_item(self):
val = len(self.arr) - 1
result = binary_search(self.arr, val)
self.assertEqual(result, val,
f'Result {result} is not {val} as expected')
def run(G):
def find_max_flow(flow):
path = bfs_path(G, s, t, condition=min_weight(flow))
return SelectAndMore((flow, path)) if path != None else Less
min, max = min_max(map(weight, G.E))
max_flow, path = binary_search(min, max, find_max_flow)
return max_flow
def exponential_search(collection, search_value):
"""Return element's index if predicate is true.
Implementation of an iterative version of the algorithm
Args:
collection: sorted indexed collection
search_value: search element
Returns:
index (int): index elementa if it exist, else -1
"""
length = len(collection)
if length == 0:
return -1
if collection[0] == search_value:
return 0
index = 1
while index < length and collection[index] <= search_value:
index *= 2
return binary_search(collection[:index], search_value)
def test_find_first_element(self):
val = 0
result = binary_search(self.arr, val)
self.assertEqual(result, 0, f'Result {result} is not 0 as expected')
def test_find_non_existent(self):
val = random.randint(1, 100) * -1
result = binary_search(self.arr, val)
self.assertIsNone(result, f'Result {result} not None as expected')
def test_find_value_in_array(self):
val = random.randint(0, len(self.arr) - 1)
pos = binary_search(self.arr, val)
self.assertEqual(val, pos, f'Result {pos} not equal to expected {val}')
def test_binary_search(input_list, item, result):
assert binary_search(input_list, item) == result
def test_binary_search_invalid(input_list, item):
assert binary_search(input_list, item) is None
def test_simple(self):
assert binary_search([x for x in range(10000)],
26) == 26, "Expected value (26) was not returned"
def test_not_found(self):
assert binary_search([1, 2, 3, 4],
5) == -1, "Expected value (-1) was not returned"
