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time_test.py
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time_test.py
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from typing import List, Callable
from geometry import Point, Rectangle
from gen_data import *
from timeit import default_timer
from kd_tree import KDTree
from quadtree import Quadtree
def test_kd_buildup(points: List[Point]) -> float:
start_time = default_timer()
_ = KDTree(points)
end_time = default_timer()
return end_time - start_time
def test_quadtree_buildup(points: List[Point]) -> float:
start_time = default_timer()
_ = Quadtree(points)
end_time = default_timer()
return end_time - start_time
def test_kd_search(points: List[Point], rectangles: List[Rectangle]) -> List[float]:
tree = KDTree(points)
def time_individual(rectangle: Rectangle) -> float:
min_x, max_x, min_y, max_y = rectangle.to_tuple()
start_time = default_timer()
tree.search(min_x, max_x, min_y, max_y)
end_time = default_timer()
return end_time - start_time
return list(map(time_individual, rectangles))
def test_quadtree_search(points: List[Point], rectangles: List[Rectangle]) -> List[float]:
tree = Quadtree(points)
def time_individual(rectangle: Rectangle) -> float:
start_time = default_timer()
tree.find(rectangle)
end_time = default_timer()
return end_time - start_time
return list(map(time_individual, rectangles))
class Tester:
def __init__(self, n_values: List[int], rectangle_amount_per_test: int, scope: Tuple[float, float] = (0, 100)):
self.n_values: List[int] = n_values
self.test_points: List[List[Point]] = list(map(lambda n: gen_points(scope=scope, n=n), self.n_values))
self.test_rectangles: List[List[Rectangle]] = [
[gen_rect(scope=scope) for _ in range(rectangle_amount_per_test)] for _ in range(len(self.n_values))
]
def print_tests_csv(
self,
buildup_tester: Callable[[List[Point]], float],
search_tester: Callable[[List[Point], List[Rectangle]], List[float]],
filename: str
):
buildup_results: List[float] = list(map(buildup_tester, self.test_points))
search_results: List[float] = [
sum(search_tester(self.test_points[i], self.test_rectangles[i])) / len(self.test_rectangles[0])
for i in range(len(self.test_points))
]
with open(filename + '_buildup.csv', 'w') as file:
file.write('n;time\n')
for i in range(len(buildup_results)):
file.write(str(self.n_values[i]) + ';' + str(buildup_results[i]) + '\n')
with open(filename + '_search.csv', 'w') as file:
file.write('n;mean_time\n')
for i in range(len(search_results)):
file.write(str(self.n_values[i]) + ';' + str(search_results[i]) + '\n')
def print_tests_both_trees_csv(self, base_filename: str):
self.print_tests_csv(test_quadtree_buildup, test_quadtree_search, base_filename + '_quadtree')
self.print_tests_csv(test_kd_buildup, test_kd_search, base_filename + '_kd_tree')
class TesterCluster(Tester):
def __init__(self,
n_values: List[int],
rectangle_amount_per_test: int,
scope: Tuple[float, float] = (0, 100),
cluster_amount: int = 5,
cluster_radius: float = 5
):
super().__init__(n_values, rectangle_amount_per_test, scope)
self.test_points = list(
map(
lambda n: gen_point_clusters(
scope=scope,
points_per_cluster=n//cluster_amount,
cluster_amount=cluster_amount,
cluster_radius=cluster_radius
),
self.n_values
)
)