geometric_series_runtime.py

from __future__ import division

from random import randint
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd


SAMPLES_PER_N_VALUE = 10000
N_VALUES = [2**n for n in (range(10))]
sns.set()

def __has_mod(A, mod=2):
    for i in range(len(A)):
        if (A[i] % mod) == 0:
            return i + 1
    return len(A)

data = []
for N in N_VALUES:
    for mod in (2, 3, 5, 10):
        current_score = 0
        for _ in range(SAMPLES_PER_N_VALUE):
            A = [randint(0, 1000000) for _ in range(N)]
            current_score += __has_mod(A, mod)
        data.append([
            N,
            'mod={}'.format(mod),
            current_score/SAMPLES_PER_N_VALUE,
        ])

data=pd.DataFrame(
    columns=[
        "N",
        "Modulus",
        "Avg runtime (over {} iterations)".format(SAMPLES_PER_N_VALUE),
    ],
    data=data,
)

ax = sns.lineplot(
    x="N",
    y="Avg runtime (over {} iterations)".format(SAMPLES_PER_N_VALUE),
    hue="Modulus",
    style="Modulus",
    data=data,
    )

plt.show()