250 lines
8.7 KiB
Python
250 lines
8.7 KiB
Python
import time
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import random
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import csv
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import matplotlib.pyplot as plt
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import numpy as np
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def ll_insert(head, name, phone):
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new_node = {'name': name, 'phone': phone, 'next': None}
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if head is None:
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return new_node
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current = head
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while current:
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if current['name'] == name:
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current['phone'] = phone
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return head
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if current['next'] is None:
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current['next'] = new_node
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return head
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current = current['next']
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return head
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def ll_find(head, name):
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current = head
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while current:
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if current['name'] == name:
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return current['phone']
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current = current['next']
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return None
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def ll_delete(head, name):
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if head is None:
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return None
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if head['name'] == name:
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return head['next']
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current = head
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while current['next']:
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if current['next']['name'] == name:
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current['next'] = current['next']['next']
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return head
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current = current['next']
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return head
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def ll_list_all(head):
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records = []
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current = head
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while current:
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records.append((current['name'], current['phone']))
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current = current['next']
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return sorted(records, key=lambda x: x[0])
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def hash_func(name, size):
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return sum(ord(c) for c in name) % size
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def ht_create(size=1000):
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return [None] * size
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def ht_insert(table, name, phone):
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idx = hash_func(name, len(table))
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table[idx] = ll_insert(table[idx], name, phone)
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def ht_find(table, name):
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idx = hash_func(name, len(table))
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return ll_find(table[idx], name)
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def ht_delete(table, name):
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idx = hash_func(name, len(table))
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table[idx] = ll_delete(table[idx], name)
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def ht_list_all(table):
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records = []
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for bucket in table:
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current = bucket
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while current:
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records.append((current['name'], current['phone']))
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current = current['next']
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return sorted(records, key=lambda x: x[0])
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def bst_insert(root, name, phone):
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if root is None:
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return {'name': name, 'phone': phone, 'left': None, 'right': None}
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if name < root['name']:
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root['left'] = bst_insert(root['left'], name, phone)
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elif name > root['name']:
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root['right'] = bst_insert(root['right'], name, phone)
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else:
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root['phone'] = phone
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return root
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def bst_find(root, name):
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if root is None:
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return None
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if name == root['name']:
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return root['phone']
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elif name < root['name']:
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return bst_find(root['left'], name)
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else:
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return bst_find(root['right'], name)
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def bst_min(node):
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while node and node['left']:
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node = node['left']
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return node
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def bst_delete(root, name):
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if root is None:
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return None
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if name < root['name']:
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root['left'] = bst_delete(root['left'], name)
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elif name > root['name']:
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root['right'] = bst_delete(root['right'], name)
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else:
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if root['left'] is None:
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return root['right']
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if root['right'] is None:
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return root['left']
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min_node = bst_min(root['right'])
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root['name'] = min_node['name']
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root['phone'] = min_node['phone']
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root['right'] = bst_delete(root['right'], min_node['name'])
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return root
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def bst_list_all(root):
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records = []
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if root:
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records.extend(bst_list_all(root['left']))
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records.append((root['name'], root['phone']))
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records.extend(bst_list_all(root['right']))
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return records
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def generate_data(n=2000):
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random_data = [(f"User_{i:05d}", str(i)) for i in range(n)]
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random.shuffle(random_data)
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sorted_data = sorted(random_data, key=lambda x: x[0])
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return random_data, sorted_data
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def run_test(data, struct_name, create, insert, find, delete):
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times = {'insert': [], 'search': [], 'delete': []}
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for _ in range(5):
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s = create()
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start = time.perf_counter()
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if struct_name == 'LinkedList' or struct_name == 'BST':
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for name, phone in data:
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s = insert(s, name, phone)
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else:
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for name, phone in data:
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insert(s, name, phone)
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times['insert'].append(time.perf_counter() - start)
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names = [random.choice(data)[0] for _ in range(100)] + [f"None_{i}" for i in range(10)]
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start = time.perf_counter()
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for name in names:
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find(s, name)
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times['search'].append(time.perf_counter() - start)
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del_names = [random.choice(data)[0] for _ in range(50)]
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start = time.perf_counter()
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for name in del_names:
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if struct_name == 'LinkedList' or struct_name == 'BST':
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s = delete(s, name)
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else:
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delete(s, name)
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times['delete'].append(time.perf_counter() - start)
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return {op: sum(t)/len(t) for op, t in times.items()}
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def plot_results(data_matrix):
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structures = ['LinkedList', 'HashTable', 'BST']
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operations = ['insert', 'search', 'delete']
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modes = ['random', 'sorted']
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fig, axes = plt.subplots(2, 2, figsize=(14, 12))
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x = np.arange(len(structures))
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width = 0.25
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for i, op in enumerate(operations):
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values = [data_matrix[s]['random'][op] for s in structures]
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axes[0,0].bar(x + i*width, values, width, label=op)
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axes[0,0].set_xlabel('Структура данных')
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axes[0,0].set_ylabel('Время (секунды)')
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axes[0,0].set_title('Случайный порядок данных')
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axes[0,0].set_xticks(x + width, structures)
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axes[0,0].legend()
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axes[0,0].grid(True, alpha=0.3)
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for i, op in enumerate(operations):
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values = [data_matrix[s]['sorted'][op] for s in structures]
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axes[0,1].bar(x + i*width, values, width, label=op)
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axes[0,1].set_xlabel('Структура данных')
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axes[0,1].set_ylabel('Время (секунды)')
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axes[0,1].set_title('Отсортированный порядок данных')
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axes[0,1].set_xticks(x + width, structures)
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axes[0,1].legend()
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axes[0,1].grid(True, alpha=0.3)
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x = np.arange(len(operations))
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width = 0.35
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for i, mode in enumerate(modes):
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values = [data_matrix['BST'][mode][op] for op in operations]
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axes[1,0].bar(x + i*width, values, width, label=mode)
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axes[1,0].set_xlabel('Операция')
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axes[1,0].set_ylabel('Время (секунды)')
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axes[1,0].set_title('BST: влияние порядка данных')
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axes[1,0].set_xticks(x + width/2, operations)
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axes[1,0].legend()
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axes[1,0].grid(True, alpha=0.3)
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for struct in structures:
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times_random = [data_matrix[struct]['random'][op] for op in operations]
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times_sorted = [data_matrix[struct]['sorted'][op] for op in operations]
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axes[1,1].plot(operations, times_random, marker='o', label=f'{struct} случайный')
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axes[1,1].plot(operations, times_sorted, marker='s', linestyle='--', label=f'{struct} отсортированный')
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axes[1,1].set_yscale('log')
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axes[1,1].set_xlabel('Операция')
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axes[1,1].set_ylabel('Время (секунды) - логарифмическая шкала')
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axes[1,1].set_title('Сравнение производительности')
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axes[1,1].legend()
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axes[1,1].grid(True, alpha=0.3)
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plt.tight_layout()
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plt.savefig('performance_graphs.png')
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plt.show()
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random_data, sorted_data = generate_data(2000)
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structs = [
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('LinkedList', lambda: None, ll_insert, ll_find, ll_delete),
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('HashTable', lambda: ht_create(2000), ht_insert, ht_find, ht_delete),
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('BST', lambda: None, bst_insert, bst_find, bst_delete)
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]
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data_matrix = {'LinkedList': {'random': {}, 'sorted': {}},
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'HashTable': {'random': {}, 'sorted': {}},
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'BST': {'random': {}, 'sorted': {}}}
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for name, create, insert, find, delete in structs:
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for order, data in [('random', random_data), ('sorted', sorted_data)]:
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times = run_test(data, name, create, insert, find, delete)
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data_matrix[name][order] = times
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with open('results.csv', 'w', newline='') as f:
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writer = csv.writer(f)
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writer.writerow(['структура', 'порядок_данных', 'операция', 'время_секунды'])
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for name in ['LinkedList', 'HashTable', 'BST']:
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for order in ['random', 'sorted']:
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for op in ['insert', 'search', 'delete']:
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writer.writerow([name, order, op, data_matrix[name][order][op]])
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plot_results(data_matrix)
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print("\n РЕЗУЛЬТАТЫ")
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for name in ['LinkedList', 'HashTable', 'BST']:
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for order in ['random', 'sorted']:
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print(f"{name} {order}: вставка={data_matrix[name][order]['insert']:.6f}, поиск={data_matrix[name][order]['search']:.6f}, удаление={data_matrix[name][order]['delete']:.6f}") |