Reaction Time Study

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap

np.random.seed(2222)
intensity = np.random.uniform(10, 100, 5500)
reaction = 400 - 2 * intensity + np.random.exponential(50, 5500)

fig, ax = plt.subplots(figsize=(10, 8), facecolor='#0a0a12')
ax.set_facecolor('#0a0a12')

colors = ['#0a0a12', '#1a1a32', '#2a2a52', '#4a4a82', '#6a6ab2', '#8a8ae2', '#aaaaff', '#ccccff']
cmap = LinearSegmentedColormap.from_list('lavender', colors, N=256)

hb = ax.hexbin(intensity, reaction, gridsize=28, cmap=cmap, mincnt=1, edgecolors='none')

cbar = plt.colorbar(hb, ax=ax, pad=0.02, shrink=0.8)
cbar.ax.set_facecolor('#0a0a12')
cbar.outline.set_edgecolor('#2a2a52')
cbar.ax.tick_params(colors='#8a8ae2', labelsize=9)
cbar.set_label('Trials', color='#8a8ae2', fontsize=10)

ax.set_xlabel('Stimulus Intensity (%)', color='#8a8ae2', fontsize=11)
ax.set_ylabel('Reaction Time (ms)', color='#8a8ae2', fontsize=11)
ax.tick_params(colors='#8a8ae2', labelsize=10)
for spine in ax.spines.values():
    spine.set_visible(False)

plt.tight_layout()