add plots

SobolevNS/docs/data/task1_data_structures/docs/data/results.csv

@@ -0,0 +1,112 @@
+Структура,Режим,Операция,N,Trial,Время (сек)
+LinkedList,shuffled,insert,10000,1,3.995075
+LinkedList,shuffled,insert,10000,2,4.133491
+LinkedList,shuffled,insert,10000,3,4.067831
+LinkedList,shuffled,insert,10000,4,4.075638
+LinkedList,shuffled,insert,10000,5,4.059367
+LinkedList,shuffled,find,10000,1,0.037171
+LinkedList,shuffled,find,10000,2,0.035212
+LinkedList,shuffled,find,10000,3,0.040434
+LinkedList,shuffled,find,10000,4,0.030968
+LinkedList,shuffled,find,10000,5,0.033432
+LinkedList,shuffled,delete,10000,1,0.014029
+LinkedList,shuffled,delete,10000,2,0.016408
+LinkedList,shuffled,delete,10000,3,0.017498
+LinkedList,shuffled,delete,10000,4,0.013770
+LinkedList,shuffled,delete,10000,5,0.016273
+LinkedList,sorted,insert,10000,1,3.083864
+LinkedList,sorted,insert,10000,2,3.123097
+LinkedList,sorted,insert,10000,3,3.084625
+LinkedList,sorted,insert,10000,4,3.200015
+LinkedList,sorted,insert,10000,5,3.124164
+LinkedList,sorted,find,10000,1,0.029411
+LinkedList,sorted,find,10000,2,0.029928
+LinkedList,sorted,find,10000,3,0.027749
+LinkedList,sorted,find,10000,4,0.032859
+LinkedList,sorted,find,10000,5,0.032080
+LinkedList,sorted,delete,10000,1,0.016454
+LinkedList,sorted,delete,10000,2,0.013526
+LinkedList,sorted,delete,10000,3,0.015424
+LinkedList,sorted,delete,10000,4,0.014688
+LinkedList,sorted,delete,10000,5,0.012838
+HashTable,shuffled,insert,10000,1,0.007074
+HashTable,shuffled,insert,10000,2,0.006665
+HashTable,shuffled,insert,10000,3,0.007361
+HashTable,shuffled,insert,10000,4,0.007405
+HashTable,shuffled,insert,10000,5,0.007248
+HashTable,shuffled,find,10000,1,0.000072
+HashTable,shuffled,find,10000,2,0.000062
+HashTable,shuffled,find,10000,3,0.000063
+HashTable,shuffled,find,10000,4,0.000062
+HashTable,shuffled,find,10000,5,0.000066
+HashTable,shuffled,delete,10000,1,0.000037
+HashTable,shuffled,delete,10000,2,0.000034
+HashTable,shuffled,delete,10000,3,0.000032
+HashTable,shuffled,delete,10000,4,0.000030
+HashTable,shuffled,delete,10000,5,0.000032
+HashTable,sorted,insert,10000,1,0.007131
+HashTable,sorted,insert,10000,2,0.006610
+HashTable,sorted,insert,10000,3,0.006701
+HashTable,sorted,insert,10000,4,0.006979
+HashTable,sorted,insert,10000,5,0.008910
+HashTable,sorted,find,10000,1,0.000065
+HashTable,sorted,find,10000,2,0.000056
+HashTable,sorted,find,10000,3,0.000068
+HashTable,sorted,find,10000,4,0.000066
+HashTable,sorted,find,10000,5,0.000076
+HashTable,sorted,delete,10000,1,0.000036
+HashTable,sorted,delete,10000,2,0.000037
+HashTable,sorted,delete,10000,3,0.000038
+HashTable,sorted,delete,10000,4,0.000045
+HashTable,sorted,delete,10000,5,0.000042
+BST,shuffled,insert,10000,1,0.018043
+BST,shuffled,insert,10000,2,0.019312
+BST,shuffled,insert,10000,3,0.017282
+BST,shuffled,insert,10000,4,0.021092
+BST,shuffled,insert,10000,5,0.016847
+BST,shuffled,find,10000,1,0.000157
+BST,shuffled,find,10000,2,0.000210
+BST,shuffled,find,10000,3,0.000168
+BST,shuffled,find,10000,4,0.000138
+BST,shuffled,find,10000,5,0.000193
+BST,shuffled,delete,10000,1,0.000129
+BST,shuffled,delete,10000,2,0.000147
+BST,shuffled,delete,10000,3,0.000122
+BST,shuffled,delete,10000,4,0.000161
+BST,shuffled,delete,10000,5,0.000128
+BST,sorted,insert,2000,1,0.123235
+BST,sorted,insert,2000,2,0.118658
+BST,sorted,insert,2000,3,0.119944
+BST,sorted,insert,2000,4,0.121595
+BST,sorted,insert,2000,5,0.116209
+BST,sorted,find,2000,1,0.005019
+BST,sorted,find,2000,2,0.005133
+BST,sorted,find,2000,3,0.005032
+BST,sorted,find,2000,4,0.004812
+BST,sorted,find,2000,5,0.004964
+BST,sorted,delete,2000,1,0.008319
+BST,sorted,delete,2000,2,0.007798
+BST,sorted,delete,2000,3,0.007584
+BST,sorted,delete,2000,4,0.008061
+BST,sorted,delete,2000,5,0.007642
+
+--- СРЕДНИЕ ---
+Структура,Режим,Операция,N,Среднее (сек),Все замеры (сек)
+LinkedList,shuffled,insert,10000,4.066280,3.995075;4.133491;4.067831;4.075638;4.059367
+LinkedList,shuffled,find,10000,0.035443,0.037171;0.035212;0.040434;0.030968;0.033432
+LinkedList,shuffled,delete,10000,0.015596,0.014029;0.016408;0.017498;0.013770;0.016273
+LinkedList,sorted,insert,10000,3.123153,3.083864;3.123097;3.084625;3.200015;3.124164
+LinkedList,sorted,find,10000,0.030406,0.029411;0.029928;0.027749;0.032859;0.032080
+LinkedList,sorted,delete,10000,0.014586,0.016454;0.013526;0.015424;0.014688;0.012838
+HashTable,shuffled,insert,10000,0.007151,0.007074;0.006665;0.007361;0.007405;0.007248
+HashTable,shuffled,find,10000,0.000065,0.000072;0.000062;0.000063;0.000062;0.000066
+HashTable,shuffled,delete,10000,0.000033,0.000037;0.000034;0.000032;0.000030;0.000032
+HashTable,sorted,insert,10000,0.007266,0.007131;0.006610;0.006701;0.006979;0.008910
+HashTable,sorted,find,10000,0.000066,0.000065;0.000056;0.000068;0.000066;0.000076
+HashTable,sorted,delete,10000,0.000040,0.000036;0.000037;0.000038;0.000045;0.000042
+BST,shuffled,insert,10000,0.018515,0.018043;0.019312;0.017282;0.021092;0.016847
+BST,shuffled,find,10000,0.000173,0.000157;0.000210;0.000168;0.000138;0.000193
+BST,shuffled,delete,10000,0.000138,0.000129;0.000147;0.000122;0.000161;0.000128
+BST,sorted,insert,2000,0.119928,0.123235;0.118658;0.119944;0.121595;0.116209
+BST,sorted,find,2000,0.004992,0.005019;0.005133;0.005032;0.004812;0.004964
+BST,sorted,delete,2000,0.007881,0.008319;0.007798;0.007584;0.008061;0.007642

SobolevNS/docs/data/task1_data_structures/plot_results.py

@@ -0,0 +1,118 @@
+"""
+plot_results.py - строит столбчатые диаграммы по итогам экспериментов.
+"""
+import csv
+import os
+import matplotlib.pyplot as plt
+import numpy as np
+
+CSV = os.path.join("docs", "data", "results.csv")
+PLOTS_DIR = os.path.join("docs", "data", "plots")
+os.makedirs(PLOTS_DIR, exist_ok=True)
+
+
+def load_means():
+    """Возвращает dict[(structure, mode, op)] = (mean, N)."""
+    means = {}
+    with open(CSV, encoding="utf-8") as f:
+        rows = list(csv.reader(f))
+    # ищем секцию "--- СРЕДНИЕ ---"
+    start = None
+    for i, row in enumerate(rows):
+        if row and row[0] == "--- СРЕДНИЕ ---":
+            start = i + 2  # пропустить заголовок секции
+            break
+    for row in rows[start:]:
+        if not row:
+            continue
+        structure, mode, op, n, mean, _trials = row
+        means[(structure, mode, op)] = (float(mean), int(n))
+    return means
+
+
+def plot_grouped(means, op, fname, title):
+    """Сгруппированные столбцы: для каждой структуры - два столбца (shuffled / sorted)."""
+    structures = ["LinkedList", "HashTable", "BST"]
+    modes = ["shuffled", "sorted"]
+    x = np.arange(len(structures))
+    width = 0.36
+
+    fig, ax = plt.subplots(figsize=(8, 5))
+
+    for i, mode in enumerate(modes):
+        vals_ms = []
+        labels = []
+        for s in structures:
+            mean, n = means[(s, mode, op)]
+            vals_ms.append(mean * 1000)
+            labels.append(f"N={n}")
+        bars = ax.bar(x + (i - 0.5) * width, vals_ms, width,
+                      label=mode, alpha=0.85)
+        for bar, lab in zip(bars, labels):
+            h = bar.get_height()
+            ax.text(bar.get_x() + bar.get_width() / 2, h,
+                    f"{h:.2f}\n{lab}", ha="center", va="bottom", fontsize=8)
+
+    ax.set_xticks(x)
+    ax.set_xticklabels(structures)
+    ax.set_ylabel("Время, мс (среднее по 5 запускам)")
+    ax.set_title(title)
+    ax.set_yscale("log")
+    ax.legend(title="порядок входных данных")
+    ax.grid(axis="y", linestyle="--", alpha=0.4)
+    plt.tight_layout()
+    out = os.path.join(PLOTS_DIR, fname)
+    plt.savefig(out, dpi=130)
+    plt.close()
+    print("saved:", out)
+
+
+def plot_bst_degradation(means, fname):
+    """Отдельный график: BST shuffled vs sorted - даже при меньшем N
+    отсортированные данные дают намного большее время."""
+    ops = ["insert", "find", "delete"]
+    shuffled = [means[("BST", "shuffled", op)][0] * 1000 for op in ops]
+    sorted_  = [means[("BST", "sorted",   op)][0] * 1000 for op in ops]
+    n_shuf   = means[("BST", "shuffled", "insert")][1]
+    n_sort   = means[("BST", "sorted",   "insert")][1]
+
+    x = np.arange(len(ops))
+    width = 0.36
+    fig, ax = plt.subplots(figsize=(7, 4.5))
+    ax.bar(x - width/2, shuffled, width, label=f"shuffled (N={n_shuf})")
+    ax.bar(x + width/2, sorted_,  width, label=f"sorted (N={n_sort})")
+    for i, v in enumerate(shuffled):
+        ax.text(i - width/2, v, f"{v:.2f}", ha="center", va="bottom", fontsize=9)
+    for i, v in enumerate(sorted_):
+        ax.text(i + width/2, v, f"{v:.2f}", ha="center", va="bottom", fontsize=9)
+
+    ax.set_xticks(x); ax.set_xticklabels(ops)
+    ax.set_ylabel("Время, мс")
+    ax.set_title("BST: деградация на отсортированных данных\n"
+                 "(N для sorted в 5 раз меньше, но время больше)")
+    ax.set_yscale("log")
+    ax.legend()
+    ax.grid(axis="y", linestyle="--", alpha=0.4)
+    plt.tight_layout()
+    out = os.path.join(PLOTS_DIR, fname)
+    plt.savefig(out, dpi=130)
+    plt.close()
+    print("saved:", out)
+
+
+def main():
+    means = load_means()
+    plot_grouped(means, "insert",
+                 "insert_compare.png",
+                 "Вставка всех записей (лог. шкала)")
+    plot_grouped(means, "find",
+                 "find_compare.png",
+                 "Поиск 110 ключей (лог. шкала)")
+    plot_grouped(means, "delete",
+                 "delete_compare.png",
+                 "Удаление 50 записей (лог. шкала)")
+    plot_bst_degradation(means, "bst_degradation.png")
+
+
+if __name__ == "__main__":
+    main()