Residual Analysis

import matplotlib.pyplot as plt
import numpy as np

# === STYLE CONFIG ===
COLORS = {
    'points': '#8B5CF6',
    'trend': '#1E293B',
    'positive': '#10B981',
    'negative': '#EF4444',
    'background': '#FFFFFF',
    'text': '#1E293B',
    'text_muted': '#64748B',
    'grid': '#F1F5F9',
}

# === DATA ===
np.random.seed(42)
x = np.linspace(1, 10, 35)
y_true = 3 * x + 5
y = y_true + np.random.normal(0, 3, 35)
residuals = y - y_true

# === FIGURE ===
fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 8), dpi=100, 
                                height_ratios=[2, 1], sharex=True)
for ax in [ax1, ax2]:
    ax.set_facecolor(COLORS['background'])
fig.patch.set_facecolor(COLORS['background'])

# === MAIN PLOT ===
# Trend line
ax1.plot(x, y_true, color=COLORS['trend'], linewidth=2, label='True relationship', zorder=2)

# Points with residual coloring
colors = [COLORS['positive'] if r >= 0 else COLORS['negative'] for r in residuals]
ax1.scatter(x, y, s=120, c=colors, alpha=0.15, zorder=3)
ax1.scatter(x, y, s=50, c=colors, alpha=0.8,
            edgecolors='white', linewidths=1.5, zorder=4)

# Residual lines
for xi, yi, yt in zip(x, y, y_true):
    ax1.plot([xi, xi], [yi, yt], color=COLORS['text_muted'], 
             linewidth=1, alpha=0.4, zorder=1)

ax1.set_ylabel('Value', fontsize=10, color=COLORS['text'], labelpad=10)

# === RESIDUAL PLOT ===
ax2.axhline(0, color=COLORS['trend'], linewidth=1.5, zorder=1)
ax2.scatter(x, residuals, s=100, c=colors, alpha=0.15, zorder=2)
ax2.scatter(x, residuals, s=40, c=colors, alpha=0.8,
            edgecolors='white', linewidths=1.5, zorder=3)

ax2.set_xlabel('X', fontsize=10, color=COLORS['text'], labelpad=10)
ax2.set_ylabel('Residual', fontsize=10, color=COLORS['text'], labelpad=10)

# === STYLING ===
for ax in [ax1, ax2]:
    ax.spines['top'].set_visible(False)
    ax.spines['right'].set_visible(False)
    ax.spines['left'].set_color(COLORS['grid'])
    ax.spines['bottom'].set_color(COLORS['grid'])
    ax.yaxis.grid(True, color=COLORS['grid'], linewidth=1)
    ax.set_axisbelow(True)
    ax.tick_params(axis='both', colors=COLORS['text_muted'], labelsize=9, length=0, pad=8)

plt.tight_layout()
plt.show()