init

1_bp_biometrik.py

@@ -0,0 +1,85 @@
+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}")

2_urinalis.py

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+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'
+
+SEGMENT_HEIGHT = 0.1
+Y_MARKER = 0.6 * SEGMENT_HEIGHT
+Y_LABEL = 0.2 * SEGMENT_HEIGHT
+
+# Data
+categories = ["pH", 
+              "Berat Jenis Urin (Urine Specific Gravity)"]
+values = [8.0, 1.010]
+ranges = [(0, 14, [4.8, 7.4]), (1.005, 1.030, [1.015, 1.025])]
+colors = [[yellow, green, red],  # pH
+          [yellow, green, red]]  # Urin]
+
+fig, axes = plt.subplots(len(categories), 1, figsize=(12, 2.6))
+
+for i, ax in enumerate(axes):
+    min_val, max_val, thresholds = ranges[i]
+    value = values[i]
+    
+    # Create segments
+    # y_gap = 0.01  # {{ Removed y_gap definition }}
+    ax.set_ylim(0, 0.1)  # {{ Updated y-axis limits to remove y_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]
+        segment_width = end - start
+
+        rect = Rectangle((start, 0), segment_width, SEGMENT_HEIGHT,  # {{ Updated y-coordinate and height to remove y_gap }}
+                        facecolor=colors[i][j % len(colors[i])], linewidth=0)
+        ax.add_patch(rect)
+    
+    # Plot value marker
+    ax.scatter([value], [Y_MARKER], color="white", marker="o", s=100, zorder=3, edgecolor='gray')
+    ax.text(value, Y_LABEL, 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="bold", fontfamily='monospace')
+    ax.spines['top'].set_visible(False)
+    ax.spines['right'].set_visible(False)
+    ax.spines['left'].set_visible(False)
+
+filename = '2_urinalis.png' 
+
+plt.tight_layout()
+plt.savefig(filename, dpi=300, bbox_inches='tight')
+print(f"Image saved as {filename}")

3_pie_suggested_lifestyle.py

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+import matplotlib.pyplot as plt
+import pandas as pd
+import numpy as np
+from matplotlib.patches import Rectangle
+
+# Data for the pie chart
+labels = ['Tekanan Darah Sistolik', 'Berat Badan', 'Tekanan Darah Diastolik']
+en_labels = ['Systolic Blood Pressure', 'Weight', 'Diastolic Blood Pressure']
+values = [66.8, 18.9, 14.2]
+colors = ['#F77F7F', '#FFB84C', '#5ECCC4']  # Red, Orange, Teal
+
+# Data for the table
+current_readings = [132, 70, 88]
+target_values = ['< 130', '41,6-51,5', '< 85']
+units = ['mmHg', 'kg', 'mmHg']
+
+# Create figure with subplots
+fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 10), 
+                               gridspec_kw={'height_ratios': [1, 0.8]})
+plt.subplots_adjust(hspace=0.3)
+
+# Pie Chart
+wedges, texts, autotexts = ax1.pie(values, colors=colors, autopct='', 
+                                  startangle=90, wedgeprops={'edgecolor': 'white', 'linewidth': 1})
+
+# Title
+ax1.set_title('Kontributor Risiko Relatif\nRelative Risk Contributors', fontsize=16, fontweight='bold', pad=20)
+
+# Add custom labels outside the pie
+for i, p in enumerate(wedges):
+    ang = (p.theta2 - p.theta1)/2. + p.theta1
+    ang_rad = ang * np.pi / 180
+    x = 1.05 * np.cos(ang_rad)
+    y = 1.05 * np.sin(ang_rad)
+    
+    # Alignment based on angle
+    horizontalalignment = 'left' if x > 0 else 'right'
+    
+    # Create the label text with percentage and name
+    label = f"{values[i]}% {labels[i]}"
+    
+    # Add the label
+    ax1.annotate(label, xy=(x, y), xytext=(1*x, 1*y),
+                horizontalalignment=horizontalalignment, fontsize=12)
+
+# Equal aspect ratio ensures the pie chart is circular
+ax1.set_aspect('equal')
+ax1.axis('off')
+
+# Table
+# Hide axes for the table subplot
+ax2.axis('off')
+
+# Create table headers
+col_labels = ['Kontributor Risiko\nRisk Contributor', 'Bacaan saat ini\nCurrent reading', 
+              'Nilai Target\nTarget value', 'Satuan\nUnits']
+table_data = []
+
+# Prepare colored boxes for the legend
+for i, (label, en_label, value, target, unit) in enumerate(zip(labels, en_labels, current_readings, target_values, units)):
+    color_box = f'\n{label}\n{en_label}'
+    table_data.append([color_box, value, target, unit])
+
+# Create table
+table = ax2.table(cellText=table_data, colLabels=col_labels, loc='center',
+                 cellLoc='center', colWidths=[0.4, 0.2, 0.2, 0.2])
+
+# Format table
+table.auto_set_font_size(False)
+table.set_fontsize(10)
+table.scale(1, 2.15)
+
+# Add color boxes to the first column of each data row
+for i in range(len(table_data)):
+    cell = table[i+1, 0]  # +1 because header is row 0
+    cell.get_text().set_color('black')
+    cell.set_facecolor(colors[i])
+    cell.set_text_props(weight='bold')
+
+# Add horizontal lines
+for i in range(len(table_data)+1):
+    for j in range(len(col_labels)):
+        table[i, j].set_edgecolor('black')
+
+# Add risk information at the bottom
+risk_text = 'Risiko Hipertensi dalam 4 Tahun\nHypertension Risk in 4 Years'
+current_risk = '51,2 %'
+target_risk = '8,3 %'
+
+ax2.text(0.00, 0.1, risk_text, transform=ax2.transAxes, 
+         color='red', fontsize=12, fontweight='bold')
+ax2.text(0.45, 0.15, current_risk, transform=ax2.transAxes, 
+         color='red', fontsize=12, fontweight='bold')
+ax2.text(0.68, 0.15, target_risk, transform=ax2.transAxes, 
+         color='black', fontsize=12)
+
+filename = '3_pie_suggested_lifestyle.png'
+plt.tight_layout()
+plt.savefig(filename, dpi=300, bbox_inches='tight')
+print(f"Image saved as {filename}")