219 lines
7.3 KiB
Python
219 lines
7.3 KiB
Python
import time
|
|
import random
|
|
import csv
|
|
import matplotlib.pyplot as plt
|
|
import numpy as np
|
|
|
|
def ll_insert(head, name, phone):
|
|
new_node = {'name': name, 'phone': phone, 'next': None}
|
|
if head is None:
|
|
return new_node
|
|
current = head
|
|
while current:
|
|
if current['name'] == name:
|
|
current['phone'] = phone
|
|
return head
|
|
if current['next'] is None:
|
|
current['next'] = new_node
|
|
return head
|
|
current = current['next']
|
|
return head
|
|
|
|
def ll_find(head, name):
|
|
current = head
|
|
while current:
|
|
if current['name'] == name:
|
|
return current['phone']
|
|
current = current['next']
|
|
return None
|
|
|
|
def ll_delete(head, name):
|
|
if head is None:
|
|
return None
|
|
if head['name'] == name:
|
|
return head['next']
|
|
current = head
|
|
while current['next']:
|
|
if current['next']['name'] == name:
|
|
current['next'] = current['next']['next']
|
|
return head
|
|
current = current['next']
|
|
return head
|
|
|
|
def ll_list_all(head):
|
|
records = []
|
|
current = head
|
|
while current:
|
|
records.append((current['name'], current['phone']))
|
|
current = current['next']
|
|
return sorted(records, key=lambda x: x[0])
|
|
def hash_func(name, size):
|
|
return sum(ord(c) for c in name) % size
|
|
|
|
def ht_create(size=1000):
|
|
return [None] * size
|
|
|
|
def ht_insert(table, name, phone):
|
|
idx = hash_func(name, len(table))
|
|
table[idx] = ll_insert(table[idx], name, phone)
|
|
|
|
def ht_find(table, name):
|
|
idx = hash_func(name, len(table))
|
|
return ll_find(table[idx], name)
|
|
|
|
def ht_delete(table, name):
|
|
idx = hash_func(name, len(table))
|
|
table[idx] = ll_delete(table[idx], name)
|
|
|
|
def ht_list_all(table):
|
|
records = []
|
|
for bucket in table:
|
|
current = bucket
|
|
while current:
|
|
records.append((current['name'], current['phone']))
|
|
current = current['next']
|
|
return sorted(records, key=lambda x: x[0])
|
|
def bst_insert(root, name, phone):
|
|
if root is None:
|
|
return {'name': name, 'phone': phone, 'left': None, 'right': None}
|
|
if name < root['name']:
|
|
root['left'] = bst_insert(root['left'], name, phone)
|
|
elif name > root['name']:
|
|
root['right'] = bst_insert(root['right'], name, phone)
|
|
else:
|
|
root['phone'] = phone
|
|
return root
|
|
|
|
def bst_find(root, name):
|
|
if root is None:
|
|
return None
|
|
if name == root['name']:
|
|
return root['phone']
|
|
elif name < root['name']:
|
|
return bst_find(root['left'], name)
|
|
else:
|
|
return bst_find(root['right'], name)
|
|
|
|
def bst_min(node):
|
|
while node and node['left']:
|
|
node = node['left']
|
|
return node
|
|
|
|
def bst_delete(root, name):
|
|
if root is None:
|
|
return None
|
|
if name < root['name']:
|
|
root['left'] = bst_delete(root['left'], name)
|
|
elif name > root['name']:
|
|
root['right'] = bst_delete(root['right'], name)
|
|
else:
|
|
if root['left'] is None:
|
|
return root['right']
|
|
if root['right'] is None:
|
|
return root['left']
|
|
min_node = bst_min(root['right'])
|
|
root['name'] = min_node['name']
|
|
root['phone'] = min_node['phone']
|
|
root['right'] = bst_delete(root['right'], min_node['name'])
|
|
return root
|
|
|
|
def bst_list_all(root):
|
|
records = []
|
|
if root:
|
|
records.extend(bst_list_all(root['left']))
|
|
records.append((root['name'], root['phone']))
|
|
records.extend(bst_list_all(root['right']))
|
|
return records
|
|
def generate_data(n=2000):
|
|
random_data = [(f"User_{i:05d}", str(i)) for i in range(n)]
|
|
random.shuffle(random_data)
|
|
sorted_data = sorted(random_data, key=lambda x: x[0])
|
|
return random_data, sorted_data
|
|
def run_test(data, struct_name, create, insert, find, delete):
|
|
times = {'insert': [], 'search': [], 'delete': []}
|
|
|
|
for _ in range(5):
|
|
s = create()
|
|
|
|
start = time.perf_counter()
|
|
if struct_name == 'LinkedList' or struct_name == 'BST':
|
|
for name, phone in data:
|
|
s = insert(s, name, phone)
|
|
else:
|
|
for name, phone in data:
|
|
insert(s, name, phone)
|
|
times['insert'].append(time.perf_counter() - start)
|
|
|
|
names = [random.choice(data)[0] for _ in range(100)] + [f"None_{i}" for i in range(10)]
|
|
start = time.perf_counter()
|
|
for name in names:
|
|
find(s, name)
|
|
times['search'].append(time.perf_counter() - start)
|
|
|
|
del_names = [random.choice(data)[0] for _ in range(50)]
|
|
start = time.perf_counter()
|
|
for name in del_names:
|
|
if struct_name == 'LinkedList' or struct_name == 'BST':
|
|
s = delete(s, name)
|
|
else:
|
|
delete(s, name)
|
|
times['delete'].append(time.perf_counter() - start)
|
|
|
|
return {op: sum(t)/len(t) for op, t in times.items()}
|
|
def plot_results(data_matrix):
|
|
structures = ['LinkedList', 'HashTable', 'BST']
|
|
operations = ['insert', 'search', 'delete']
|
|
modes = ['random', 'sorted']
|
|
|
|
fig, axes = plt.subplots(2, 2, figsize=(14, 12))
|
|
|
|
x = np.arange(len(structures))
|
|
width = 0.25
|
|
|
|
for i, op in enumerate(operations):
|
|
values = [data_matrix[s]['random'][op] for s in structures]
|
|
axes[0,0].bar(x + i*width, values, width, label=op)
|
|
axes[0,0].set_xlabel('Структура данных')
|
|
axes[0,0].set_ylabel('Время (секунды)')
|
|
axes[0,0].set_title('Случайный порядок данных')
|
|
axes[0,0].set_xticks(x + width, structures)
|
|
axes[0,0].legend()
|
|
axes[0,0].grid(True, alpha=0.3)
|
|
|
|
for i, op in enumerate(operations):
|
|
values = [data_matrix[s]['sorted'][op] for s in structures]
|
|
axes[0,1].bar(x + i*width, values, width, label=op)
|
|
axes[0,1].set_xlabel('Структура данных')
|
|
axes[0,1].set_ylabel('Время (секунды)')
|
|
axes[0,1].set_title('Отсортированный порядок данных')
|
|
axes[0,1].set_xticks(x + width, structures)
|
|
axes[0,1].legend()
|
|
axes[0,1].grid(True, alpha=0.3)
|
|
|
|
x = np.arange(len(operations))
|
|
width = 0.35
|
|
for i, mode in enumerate(modes):
|
|
values = [data_matrix['BST'][mode][op] for op in operations]
|
|
axes[1,0].bar(x + i*width, values, width, label=mode)
|
|
axes[1,0].set_xlabel('Операция')
|
|
axes[1,0].set_ylabel('Время (секунды)')
|
|
axes[1,0].set_title('BST: влияние порядка данных')
|
|
axes[1,0].set_xticks(x + width/2, operations)
|
|
axes[1,0].legend()
|
|
axes[1,0].grid(True, alpha=0.3)
|
|
|
|
for struct in structures:
|
|
times_random = [data_matrix[struct]['random'][op] for op in operations]
|
|
times_sorted = [data_matrix[struct]['sorted'][op] for op in operations]
|
|
axes[1,1].plot(operations, times_random, marker='o', label=f'{struct} случайный')
|
|
axes[1,1].plot(operations, times_sorted, marker='s', linestyle='--', label=f'{struct} отсортированный')
|
|
axes[1,1].set_yscale('log')
|
|
axes[1,1].set_xlabel('Операция')
|
|
axes[1,1].set_ylabel('Время (секунды) - логарифмическая шкала')
|
|
axes[1,1].set_title('Сравнение производительности')
|
|
axes[1,1].legend()
|
|
axes[1,1].grid(True, alpha=0.3)
|
|
|
|
plt.tight_layout()
|
|
plt.savefig('performance_graphs.png')
|
|
plt.show() |