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pyplot-health-analysis/1_bp_biometrik.py
AlfandiMario 78a26bc2d0 init
2025-03-04 11:40:35 +07:00

85 lines
3.6 KiB
Python

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}")