Benchmark Wip

bench.py

import matplotlib.pyplot as plt
import time
import pandas as pd

df = pd.read_csv('sample_data.csv')

x = df['x']
y = df['y']
color = df[['color_r', 'color_g', 'color_b', 'color_a']].values


start_time = time.perf_counter()
iterations = 1
for _ in range(iterations):
    plt.scatter(x=df['x'], y=df['y'], c=color)
    plt.title('Scatter plot')
    plt.xlabel('x')
    plt.ylabel('y')
    plt.show(block=False)
end_time = time.perf_counter()

result_time = (end_time - start_time) / iterations
print(f"time: {result_time}")

data_gen.py

import numpy as np

import pandas as pd

n = 10_000_000

data = {
    'x':       np.random.rand(n),
    'y':       np.random.rand(n),
    'size':    np.random.rand(n),
    'color_r': np.random.rand(n),
    'color_g': np.random.rand(n),
    'color_b': np.random.rand(n),
    'color_a': np.random.rand(n),
}

df = pd.DataFrame(data)

df.to_csv('./sample_data.csv')