def return_avg(path_array):
location_key = return_arrays()
path_length = len(path_array)
total_danger = 0
for i in range(path_length):
location = path_array[i]
long_index = binarySearch(location_key[0], 0, len(location_key[0]),
location[0])
lat_index = binarySearch(location_key[1], 0, len(location_key[1]),
location[1])
total_danger += grid[day][hour][long_index][lat_index]
return total_danger / path_length
def test_binarySearch_Cmp(self):
data = []
for i in range(10000):
data.append(random.randint(1, 100000000))
for i in range(100):
number = random.randint(1, 100000000)
self.assertEqual(search.binarySearch(data, number),
search.binarySearchRecursive(data, number))
def test_BS(self): sa = self.assertEqual l = range(0,100000) sa(3, search.binarySearch(l, 3)) sa(9, search.binarySearch(l, 9)) sa(0, search.binarySearch(l, 0)) sa(100, search.binarySearch(l, 100)) sa(3, search.binarySearch(l, 3, "rec")) sa(9, search.binarySearch(l, 9), "rec") sa(0, search.binarySearch(l, 0), "rec") sa(100, search.binarySearch(l, 100), "rec")
def test_BS(self):
sa = self.assertEqual
l = range(0, 100000)
sa(3, search.binarySearch(l, 3))
sa(9, search.binarySearch(l, 9))
sa(0, search.binarySearch(l, 0))
sa(100, search.binarySearch(l, 100))
sa(3, search.binarySearch(l, 3, "rec"))
sa(9, search.binarySearch(l, 9), "rec")
sa(0, search.binarySearch(l, 0), "rec")
sa(100, search.binarySearch(l, 100), "rec")
from search import binarySearch # This list must be sorted. If it is not given as sorted, sort it first, then call the binarySearch method testlist = [0, 1, 2, 8, 13, 17, 19, 32, 42] print(binarySearch(3, testlist)) print(binarySearch(13, testlist))
def test_bynarySearh_1(self):
data = [1, 2, 45, 56, 100, 178, 290]
self.assertEqual(search.binarySearch(data, 100), 4)
self.assertEqual(search.binarySearch(data, 178), 5)
self.assertEqual(search.binarySearch(data, 1), 0)
self.assertEqual(search.binarySearch(data, 2), 1)
latitude_length = len(latitude_key)
baseline_matrix = [[], [], [], [], [], [], []]
for day in range(7):
for i in range(longitude_length):
baseline_matrix[day].append([])
for j in range(latitude_length):
baseline_matrix[day][i].append([])
for index, row in df_arrest_con.iterrows():
long_value = row['Longitude']
lat_value = row['Latitude']
day_of_week = int(row['ARREST_DATE'])
long_index = int(
binarySearch(longitude_key, 0, longitude_length, long_value))
lat_index = int(binarySearch(latitude_key, 0, latitude_length, lat_value))
baseline_matrix[day_of_week][long_index][lat_index].append(
(row['AGE_GROUP'], row['LAW_CAT_CD']))
grid = [[], [], [], [], [], [], []]
for day in range(7):
for hour in range(24):
grid[day].append(baseline_matrix[day])
for index, row in df_shooting_con.iterrows():
long_value = row['Longitude']
lat_value = row['Latitude']
day_of_week = int(row['OCCUR_DATE'])
hour = int(row['OCCUR_TIME'])
def test_search(self):
data = [1, 2, 3, 5, 6, 12, 7, 4, 8]
self.assertEqual(linear_search(data, 6), 4)
self.assertEqual(linear_search(data, 10), -1)
self.assertEqual(binarySearch(data, 6), 4)
import random
from search import linear_search
from time import time
from search import binarySearch
data = range(100000)
start = time()
index = binarySearch(data, data[0])
end = time()
elapsed = end - start
print('Total time elspsed for binary search is: ' + str(elapsed))
datalin = random.sample(range(1000), 1000)
startlin = time()
length = int(len(datalin) / 2)
indexlin = linear_search(datalin, datalin[length])
endlin = time()
elapsedlin = endlin - startlin
print('Total time elapsed for linear search is: ' + str(elapsedlin))