import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import FancyBboxPatch, Rectangle
from matplotlib.colors import LinearSegmentedColormap

# Color scheme
green = '#8DC58D'
yellow = '#FBBC78'
red = '#F77F7F'
gray = '#DDDDDD'
light_blue = '#D9E8F5'
light_gray = '#F5F5F5'

# Data
categories = ["Resiko Hipertensi dalam 4 tahun (Hypertension Risk in 4 years)", 
              "Lingkar Pinggang (Waist Circumference)", "Tekanan Darah Sistolik (Systolic BP)", 
              "Tekanan Darah Diastolik (Diastolic BP)", "Indeks Massa Tubuh (BMI)"]
values = [51.17, 93.0, 132.0, 88.0, 31.11]
ranges = [(0, 100, [5, 10]), (60, 120, [80]), (70, 180, [90, 130, 140]), (50, 120, [60, 85, 90]), (15, 40, [18.5, 23, 25, 30])]
colors = [[green, yellow, red],  # Hypertension
          [green, red],          # Waist
          [yellow, green, yellow, red],   # Systolic BP
          [yellow, green, yellow, red],   # Diastolic BP
          [yellow, green, yellow, red, red]]   # BMI

fig, axes = plt.subplots(len(categories), 1, figsize=(12, 7))

for i, ax in enumerate(axes):
    min_val, max_val, thresholds = ranges[i]
    value = values[i]
    
    # First create a background bar (gray) with rounded corners
    bg_rect = FancyBboxPatch((min_val, 0), max_val - min_val, 0.1,
                          boxstyle="round,pad=0.01", 
                          facecolor=gray, alpha=0.3, linewidth=0)
    ax.add_patch(bg_rect)
    
    # Create segments
    y_gap = 0.01  # Define the gap between segments on the y-axis
    ax.set_ylim(-y_gap, 0.1 + y_gap)  # Adjust the y-axis limits to include the gap
    all_points = [min_val] + thresholds + [max_val]
    for j in range(len(all_points)-1):
        start = all_points[j]
        end = all_points[j+1]

        if i == 0:  # Apply gradient only for the first chart's first segment
            # Define the gradient colormap
            gradient_cmap = LinearSegmentedColormap.from_list("gradient", [gray, colors[i][j]], N=256)
            
            # Create a gradient rectangle usingimshow
            gradient_width = value - start
            if gradient_width > 0:
                gradient_rect = plt.Rectangle((start, y_gap), gradient_width, 0.1 - 2*y_gap, facecolor=gradient_cmap(0.9), linewidth=0)
                ax.add_patch(gradient_rect)
            
            # Fill the remaining part with gray
            remaining_width = end - max(value, start)
            if remaining_width > 0:
                remaining_rect = plt.Rectangle((max(value, start), y_gap), remaining_width, 0.1 - 2*y_gap, facecolor=gray, linewidth=0)
                ax.add_patch(remaining_rect)
        else:
            segment_width = end - start
            rect = Rectangle((start, y_gap), segment_width, 0.1 - 2*y_gap,
                            facecolor=colors[i][j % len(colors[i])], linewidth=0)
            ax.add_patch(rect)
    
    # Plot value marker
    ax.scatter([value], [0.06], color="white", marker="o", s=100, zorder=3, edgecolor='gray')
    ax.text(value, 0.02, f"{value:.1f}", ha="center", fontsize=10, color="black", weight="bold", 
            fontfamily='monospace')
    
    # Axis formatting - properly align ticks with segment boundaries
    ax.set_xlim(min_val, max_val)
    ax.set_yticks([])
    ax.set_xticks(all_points)  # Set ticks at exact boundary points
    ax.set_title(categories[i], fontsize=12, weight="normal", fontfamily='sans-serif')
    ax.spines['top'].set_visible(False)
    ax.spines['right'].set_visible(False)
    ax.spines['left'].set_visible(False)

filename = '1_bp_biometrik.png'

plt.tight_layout()
plt.savefig(filename, dpi=300, bbox_inches='tight')
print(f"Image saved as {filename}")