scripts/result_viewer_meanstd.py - main - GraphTreeHeap/museumdb2_experiments

scripts/result_viewer_meanstd.py
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FedMam
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25 май 2026, 19:18
25 май 2026, 19:18a73447a
import sys
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

df_u = pd.read_csv('uniform-final.csv')
df_c = pd.read_csv('clusters-final.csv')
df_n = pd.read_csv('nyc-buildings-final.csv')
df_s = pd.read_csv('stellar-final.csv')
df_w = pd.read_csv('worldcities-final.csv')

fig, ax = plt.subplots()

QUERY_TYPE = 'range'
TITLE = 'Поиск точек в прямоугольнике (range)'

BAR_WIDTH = 0.2

RED    = '#E01B24'
BLUE   = '#1C71D8'
YELLOW = '#F5C211'

DATASETS = ['uniform', 'clusters', 'nyc-buildings', 'stellar', 'worldcities']
x = np.arange(len(DATASETS))

reads_u = df_u[df_u['Type'].str.startswith(QUERY_TYPE)]
reads_c = df_c[df_c['Type'].str.startswith(QUERY_TYPE)]
reads_n = df_n[df_n['Type'].str.startswith(QUERY_TYPE)]
reads_s = df_s[df_s['Type'].str.startswith(QUERY_TYPE)]
reads_w = df_w[df_w['Type'].str.startswith(QUERY_TYPE)]

mean_mdb2 = np.array([reads_u['MuseumDB2_Time'].mean(),
             reads_c['MuseumDB2_Time'].mean(),
             reads_n['MuseumDB2_Time'].mean(),
             reads_s['MuseumDB2_Time'].mean(),
             reads_w['MuseumDB2_Time'].mean()])
mean_psql = np.array([reads_u['PostgreSQL_Time'].mean(),
             reads_c['PostgreSQL_Time'].mean(),
             reads_n['PostgreSQL_Time'].mean(),
             reads_s['PostgreSQL_Time'].mean(),
             reads_w['PostgreSQL_Time'].mean()])
mean_msql = np.array([reads_u['MySQL_Time'].mean(),
             reads_c['MySQL_Time'].mean(),
             reads_n['MySQL_Time'].mean(),
             reads_s['MySQL_Time'].mean(),
             reads_w['MySQL_Time'].mean()])

std_mdb2 = np.array([reads_u['MuseumDB2_Time'].std(),
             reads_c['MuseumDB2_Time'].std(),
             reads_n['MuseumDB2_Time'].std(),
             reads_s['MuseumDB2_Time'].std(),
             reads_w['MuseumDB2_Time'].std()])
std_psql = np.array([reads_u['PostgreSQL_Time'].std(),
             reads_c['PostgreSQL_Time'].std(),
             reads_n['PostgreSQL_Time'].std(),
             reads_s['PostgreSQL_Time'].std(),
             reads_w['PostgreSQL_Time'].std()])
std_msql = np.array([reads_u['MySQL_Time'].std(),
             reads_c['MySQL_Time'].std(),
             reads_n['MySQL_Time'].std(),
             reads_s['MySQL_Time'].std(),
             reads_w['MySQL_Time'].std()])

# DEBUG
print(mean_mdb2, mean_psql, mean_msql, std_mdb2, std_psql, std_msql, sep='\n')

ax.bar(x - BAR_WIDTH, mean_mdb2, BAR_WIDTH, yerr=std_mdb2, label='MuseumDB2', color=RED)
ax.bar(x,             mean_psql, BAR_WIDTH, yerr=std_psql, label='PostGIS', color=BLUE)
ax.bar(x + BAR_WIDTH, mean_msql, BAR_WIDTH, yerr=std_msql, label='MySQL', color=YELLOW)

ax.set_xticks(x)
ax.set_xticklabels(DATASETS)
ax.set_xlabel('Датасет')
ax.set_ylabel('Время (с)')
ax.set_title(TITLE)
ax.legend(loc='upper left')

plt.tight_layout()
plt.show()