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Dict:
"""Calculate VO2 Max table data based on age and gender"""
- # VO2 Max Master Chart Data (from notebook)
+ # VO2 Max Master Chart Data (from notebook - matching exact values)
vo2_max_data = {
"20-29 (M)": {
- "Very Poor": (None, 38.1),
- "Poor": (38.1, 44.1),
- "Fair": (44.1, 51.0),
- "Good": (51.0, 56.9),
- "Excellent": (56.9, 66.3),
+ "Very Poor": (29.0, 38.1),
+ "Poor": (38.1, 44.9),
+ "Fair": (44.9, 50.2),
+ "Good": (50.2, 61.8),
+ "Excellent": (57.1, 66.3),
"Superior": (66.3, None),
},
"30-39 (M)": {
- "Very Poor": (None, 34.1),
- "Poor": (34.1, 39.5),
- "Fair": (39.5, 45.3),
- "Good": (45.3, 51.3),
- "Excellent": (51.3, 59.8),
+ "Very Poor": (27.2, 34.1),
+ "Poor": (34.1, 39.6),
+ "Fair": (39.6, 45.2),
+ "Good": (45.2, 51.6),
+ "Excellent": (51.6, 59.8),
"Superior": (59.8, None),
},
"40-49 (M)": {
- "Very Poor": (None, 30.5),
- "Poor": (30.5, 35.4),
- "Fair": (35.4, 40.9),
- "Good": (40.9, 46.3),
- "Excellent": (46.3, 55.6),
+ "Very Poor": (24.2, 30.5),
+ "Poor": (30.5, 35.7),
+ "Fair": (35.7, 40.3),
+ "Good": (40.3, 46.7),
+ "Excellent": (46.7, 55.6),
"Superior": (55.6, None),
},
"50-59 (M)": {
- "Very Poor": (None, 26.1),
- "Poor": (26.1, 30.9),
- "Fair": (30.9, 35.7),
- "Good": (35.7, 40.9),
- "Excellent": (40.9, 50.7),
+ "Very Poor": (20.9, 26.1),
+ "Poor": (26.1, 30.7),
+ "Fair": (30.7, 35.1),
+ "Good": (35.1, 41.2),
+ "Excellent": (41.2, 50.7),
"Superior": (50.7, None),
},
- "60+ (M)": {
- "Very Poor": (None, 22.4),
- "Poor": (22.4, 26.5),
- "Fair": (26.5, 32.2),
- "Good": (32.2, 36.3),
- "Excellent": (36.3, 43.0),
+ "60-69 (M)": {
+ "Very Poor": (17.4, 22.4),
+ "Poor": (22.4, 26.6),
+ "Fair": (26.6, 30.5),
+ "Good": (30.5, 36.1),
+ "Excellent": (36.1, 43.0),
"Superior": (43.0, None),
},
"20-29 (F)": {
- "Very Poor": (None, 28.6),
- "Poor": (28.6, 33.7),
- "Fair": (33.7, 38.5),
- "Good": (38.5, 43.8),
- "Excellent": (43.8, 56.0),
+ "Very Poor": (21.7, 28.6),
+ "Poor": (28.6, 34.6),
+ "Fair": (34.6, 40.6),
+ "Good": (40.6, 46.5),
+ "Excellent": (46.5, 56.0),
"Superior": (56.0, None),
},
"30-39 (F)": {
- "Very Poor": (None, 24.1),
+ "Very Poor": (19.0, 24.1),
"Poor": (24.1, 28.2),
"Fair": (28.2, 32.2),
"Good": (32.2, 35.7),
@@ -896,42 +896,50 @@ class ContextGenerator:
"Superior": (45.8, None),
},
"40-49 (F)": {
- "Very Poor": (None, 22.7),
- "Poor": (22.7, 26.5),
- "Fair": (26.5, 30.5),
- "Good": (30.5, 35.0),
- "Excellent": (35.0, 42.3),
- "Superior": (42.3, None),
+ "Very Poor": (17.0, 21.3),
+ "Poor": (21.3, 24.9),
+ "Fair": (24.9, 28.7),
+ "Good": (28.7, 34.0),
+ "Excellent": (34.0, 41.7),
+ "Superior": (41.7, None),
},
"50-59 (F)": {
- "Very Poor": (None, 21.5),
- "Poor": (21.5, 24.9),
- "Fair": (24.9, 28.7),
- "Good": (28.7, 32.9),
- "Excellent": (32.9, 40.4),
- "Superior": (40.4, None),
+ "Very Poor": (16.0, 19.1),
+ "Poor": (19.1, 24.4),
+ "Fair": (21.8, 27.6),
+ "Good": (25.2, 28.6),
+ "Excellent": (28.6, 35.9),
+ "Superior": (35.9, None),
},
- "60+ (F)": {
- "Very Poor": (None, 19.0),
- "Poor": (19.0, 22.7),
- "Fair": (22.7, 26.1),
- "Good": (26.1, 30.1),
- "Excellent": (30.1, 36.7),
- "Superior": (36.7, None),
+ "60-69 (F)": {
+ "Very Poor": (13.4, 16.5),
+ "Poor": (16.5, 18.9),
+ "Fair": (18.9, 21.2),
+ "Good": (21.2, 24.6),
+ "Excellent": (24.6, 29.4),
+ "Superior": (29.4, None),
},
}
- # Determine age bracket
- if age < 30:
+ # Determine age bracket (matching notebook logic)
+ if 20 <= age <= 29:
age_key = "20-29"
- elif age < 40:
+ elif 30 <= age <= 39:
age_key = "30-39"
- elif age < 50:
+ elif 40 <= age <= 49:
age_key = "40-49"
- elif age < 60:
+ elif 50 <= age <= 59:
age_key = "50-59"
+ elif 60 <= age <= 69:
+ age_key = "60-69"
else:
- age_key = "60+"
+ # Default to closest range
+ if age < 20:
+ age_key = "20-29"
+ elif age >= 70:
+ age_key = "60-69"
+ else:
+ age_key = "30-39" # fallback
gender_key = "(M)" if gender.lower() == "male" else "(F)"
key = f"{age_key} {gender_key}"
@@ -951,8 +959,35 @@ class ContextGenerator:
return {
"age_range": age_key,
"ranges": result,
+ "raw_ranges": ranges, # Keep raw ranges for category determination
}
+ def _determine_vo2_max_category(self, vo2_max: float, age: int, gender: str) -> str:
+ """Determine VO2 max category based on value, age, and gender (matching notebook logic)"""
+ vo2_max_table_info = self._calculate_vo2_max_table_data(age, gender)
+ ranges = vo2_max_table_info["raw_ranges"]
+
+ categories = ["Very Poor", "Poor", "Fair", "Good", "Excellent", "Superior"]
+
+ # Check Superior category first (open-ended)
+ min_val, max_val = ranges["Superior"]
+ if max_val is None and vo2_max >= min_val:
+ return "Superior"
+
+ # Check other categories from Excellent down to Very Poor
+ # Ranges are typically [min, max) - inclusive of min, exclusive of max
+ for category in reversed(
+ categories[:-1]
+ ): # Exclude Superior as we already checked it
+ min_val, max_val = ranges[category]
+ # Check if value falls in this range (inclusive of min, exclusive of max)
+ if min_val <= vo2_max < max_val:
+ return category
+
+ # If value is below all ranges, return Very Poor
+ # This handles the case where vo2_max < min of Very Poor
+ return "Very Poor"
+
def calculate_rmr_and_fuel_source(self) -> Dict:
"""Calculate RMR and fuel source from pnoe data"""
metrics = {}
@@ -1128,11 +1163,22 @@ class ContextGenerator:
self.patient_info["age"], self.patient_info["gender"]
)
+ # Determine patient's VO2 max category
+ vo2_max_value = pnoe_metrics.get("vo2_max_per_kg", 0.0)
+ category = self._determine_vo2_max_category(
+ vo2_max_value,
+ self.patient_info["age"],
+ self.patient_info["gender"],
+ )
+
# VO2 Max Table
+ gender_label = (
+ "F" if self.patient_info["gender"].lower() == "female" else "M"
+ )
+ age_range_label = f"{vo2_max_table_info['age_range']} ({gender_label})"
+
vo2_max_columns = [
- "Age (F)"
- if self.patient_info["gender"].lower() == "female"
- else "Age (M)",
+ "Age",
"Very Poor",
"Poor",
"Fair",
@@ -1142,7 +1188,7 @@ class ContextGenerator:
]
vo2_max_data = [
[
- vo2_max_table_info["age_range"],
+ age_range_label,
vo2_max_table_info["ranges"]["Very Poor"],
vo2_max_table_info["ranges"]["Poor"],
vo2_max_table_info["ranges"]["Fair"],
@@ -1151,23 +1197,13 @@ class ContextGenerator:
vo2_max_table_info["ranges"]["Superior"],
]
]
- vo2_max_colors = [
- [
- "#b2ebf2",
- "#f5f5f5",
- "#f5f5f5",
- "#f5f5f5",
- "#f5f5f5",
- "#f5f5f5",
- "#f5f5f5",
- ]
- ]
contexts["page_8"]["vo2_max_table"] = (
graph_generator.generate_vo2_max_table(
data=vo2_max_data,
columns=vo2_max_columns,
- cell_colors=vo2_max_colors,
+ vo2_max_value=vo2_max_value,
+ category=category,
save_as_base64=True,
)
)
diff --git a/app/services/graph_generator.py b/app/services/graph_generator.py
index 0245525..340d210 100644
--- a/app/services/graph_generator.py
+++ b/app/services/graph_generator.py
@@ -1310,15 +1310,19 @@ class GraphGenerator:
self,
data: list[list],
columns: list[str],
+ vo2_max_value: float = None,
+ category: str = None,
cell_colors: list[list[str]] = None,
save_as_base64: bool = True,
) -> str:
"""
- Generate VO2 Max table as an image with optimized sizing.
+ Generate VO2 Max table as an image with optimized sizing, highlighting the patient's category.
Args:
data: List of rows (each row is a list of values)
columns: List of column headers
+ vo2_max_value: Patient's VO2 max value (for title and arrow)
+ category: Category that the patient falls into (e.g., 'Good', 'Excellent')
cell_colors: Optional matrix of cell colors
save_as_base64: If True, return base64 string
@@ -1327,12 +1331,11 @@ class GraphGenerator:
"""
import io
- # Fixed optimal sizing for VO2 Max table (8 columns, 1 data row)
- fig, ax = plt.subplots(figsize=(16, 2.5))
- ax.axis("off")
+ from matplotlib.patches import FancyArrowPatch, RegularPolygon
- # Even column widths for VO2 Max table
- col_widths = [1.0 / len(columns)] * len(columns)
+ # Fixed optimal sizing for VO2 Max table (7 columns, 1 data row)
+ fig, ax = plt.subplots(figsize=(14, 3))
+ ax.axis("off")
# Create table
table = ax.table(
@@ -1340,33 +1343,87 @@ class GraphGenerator:
colLabels=columns,
cellLoc="center",
loc="center",
- colColours=["#4dd0e1"] * len(columns),
- colWidths=col_widths,
+ bbox=[0, 0, 1, 1],
)
# Style the table
table.auto_set_font_size(False)
table.set_fontsize(11)
- table.scale(1, 3.0)
+ table.scale(1, 2.5)
- # Apply cell colors
- if cell_colors:
- for i, row_colors in enumerate(cell_colors):
- for j, color in enumerate(row_colors):
- if color and j < len(columns):
- cell = table[(i + 1, j)]
- cell.set_facecolor(color)
+ # Header row styling (cyan background)
+ for i in range(len(columns)):
+ cell = table[(0, i)]
+ cell.set_facecolor("#7dd3fc") # cyan-300 equivalent
+ cell.set_text_props(weight="bold", color="black", fontsize=12)
+ cell.set_edgecolor("#9ca3af") # gray-400
+ cell.set_linewidth(1)
- # Style all cells
- for (row, col), cell in table.get_celld().items():
- if row == 0:
- cell.set_text_props(weight="bold", fontsize=12)
- cell.set_edgecolor("#333333")
- cell.set_linewidth(1.5)
+ # Find the column index for the category (if provided)
+ category_index = None
+ if category and category in columns:
+ category_index = columns.index(category)
+
+ # Data row styling
+ for i in range(len(data[0])):
+ cell = table[(1, i)]
+ if i == 0: # Age column
+ cell.set_facecolor("#a5f3fc") # cyan-200
+ cell.set_text_props(weight="semibold", color="black", fontsize=11)
else:
- cell.set_edgecolor("#666666")
- cell.set_linewidth(1.0)
- cell.set_text_props(fontsize=10)
+ cell.set_facecolor("#f3f4f6") # gray-100
+ cell.set_text_props(color="black", fontsize=10)
+ # Bold the cell that corresponds to the patient's category
+ if category_index is not None and i == category_index:
+ cell.set_text_props(weight="bold", color="black", fontsize=11)
+ cell.set_edgecolor("#9ca3af") # gray-400
+ cell.set_linewidth(1)
+
+ # Add arrow indicator below the category column
+ if category_index is not None:
+ # Calculate position
+ cell_width = 1.0 / len(columns)
+ arrow_x = (category_index + 0.5) * cell_width
+
+ # Draw arrow pointing up
+ arrow = FancyArrowPatch(
+ (arrow_x, -0.15),
+ (arrow_x, -0.05),
+ arrowstyle="->",
+ mutation_scale=20,
+ linewidth=2,
+ color="black",
+ transform=ax.transAxes,
+ )
+ ax.add_patch(arrow)
+
+ # Add triangle at the top
+ triangle = RegularPolygon(
+ (arrow_x, -0.05),
+ 3,
+ radius=0.02,
+ orientation=np.pi / 2,
+ color="black",
+ transform=ax.transAxes,
+ )
+ ax.add_patch(triangle)
+
+ # Set title - calculate approximate percentile
+ if vo2_max_value is not None:
+ if category == "Superior":
+ percentile = "100th percentile"
+ else:
+ percentile_map = {
+ "Very Poor": "1st-10th percentile",
+ "Poor": "10th-20th percentile",
+ "Fair": "20th-40th percentile",
+ "Good": "40th-60th percentile",
+ "Excellent": "60th-80th percentile",
+ }
+ percentile = percentile_map.get(category, "N/A")
+
+ title = f"VO2 Max - {vo2_max_value:.1f} ({percentile})"
+ ax.set_title(title, fontsize=14, fontweight="bold", pad=20)
if save_as_base64:
buf = io.BytesIO()
diff --git a/notebooks/graphs.ipynb b/notebooks/graphs.ipynb
index b5c88df..7d12178 100644
--- a/notebooks/graphs.ipynb
+++ b/notebooks/graphs.ipynb
@@ -2066,7 +2066,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "report-generation",
+ "display_name": ".venv",
"language": "python",
"name": "python3"
},