import matplotlib.pyplot as plt
from matplotlib.patches import Patch
import numpy as np
from scipy.interpolate import make_interp_spline

# 1. HIA Data (Probability/Fraction)
x = [0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5, 
     0.55, 0.6, 0.65, 0.7, 0.75, 0.8, 0.85, 0.9, 0.95, 1]

# Frequencies in %
y = [1.33, 2.95, 3.36, 2.31, 1.33, 1.38, 1.54, 1.17, 1.09, 1.33, 
     1.70, 2.22, 2.27, 2.47, 3.16, 3.56, 5.74, 10.56, 24.43, 26.09]

# 2. Curve smoothing (Spline)
# We use a reduced list of points for the spline to avoid oscillations at low values
x_smooth = np.linspace(min(x), max(x), 300)
spl = make_interp_spline(x, y, k=3) 
y_smooth = spl(x_smooth)
y_smooth = [val if val > 0 else 0 for val in y_smooth]

# 3. Define colors (HIA Traffic Light)
colors = []
for val in x:
    # High Absorption (> 0.7) - Zone of Excellence
    if val >= 0.7:
        colors.append('green')
    # Poor Absorption (< 0.3) - Study Criteria
    elif val < 0.3:
        colors.append('firebrick')
    # Intermediate Zone (Meets criteria >30% but it is low)
    else:
        colors.append('gold')

# 4. Create the chart
plt.figure(figsize=(7, 6))

# A. Draw Bars
plt.bar(x, y, width=0.04, color=colors, edgecolor='black', alpha=0.7, label='Data Frequency')

# 5. Tags and Titles
plt.xlabel('Human Intestinal Absorption (HIA) Score [0-1]', fontsize=12)
plt.ylabel('% Frequency', fontsize=12)
plt.title('HIA Distribution', fontsize=14)

# Adjust axes
plt.xticks(np.arange(0, 1.1, 0.1))
plt.xlim(0, 1.05)
plt.ylim(0, 30)

# 6. Custom Legend (Vertical)
legend_elements = [
    Patch(facecolor='green', edgecolor='black', alpha=0.7, label='Excellent Absorption (> 0.7)'),
    Patch(facecolor='gold', edgecolor='black', alpha=0.7, label='Passed Threshold (0.3 - 0.7)'),
    Patch(facecolor='firebrick', edgecolor='black', alpha=0.7, label='Poor Absorption (< 0.3)'),
]

plt.legend(handles=legend_elements, loc='upper left', ncol=1, framealpha=0.9)

plt.grid(axis='y', linestyle='--', alpha=0.5)
plt.tight_layout()

plt.show()