import psycopg2
import matplotlib.pyplot as plt
from mplcursors import cursor  # separate package must be installed

# Connect to your postgres DB
conn = psycopg2.connect("postgres://postgres:password@localhost:5420/postgres")

# Open a cursor to perform database operations
cur = conn.cursor()

# Execute a query
cur.execute("SELECT difficulty FROM logs_avg ORDER BY difficulty")  # LIMIT 100000")
# Retrieve query results
difficulty = cur.fetchall()

cur.execute("SELECT mean_time FROM logs_avg ORDER BY difficulty")  # LIMIT 100000")
time = cur.fetchall()


def norm(arr) -> [int]:
    elements = []
    d = 10**7
    for (a,) in arr:
        p = a / d
        elements.append(p)

    return elements


time = norm(time)
difficulty = norm(difficulty)

# reproducible sample data as a pandas dataframe
# plt.figure(figsize=(4096, 4096))
plt.scatter(difficulty, time)
# cursor(hover=True)
plt.xlabel("Difficulty Factor (1e7)")
plt.ylabel("Time (1e7 μs)")
plt.show()