fixes

Author: pawxnsingh

analysis.py

@@ -1,55 +1,47 @@
+import numpy as np
 import matplotlib.pyplot as plt
 import json
 
 def analyze_data(data):
     numbers = data.get("numbers", [])
-    
     if not numbers:
-        return {"error": "No numbers provided for analysis"}
+        return {"error": "No numbers provided"}
 
-    average = sum(numbers) / len(numbers)
-    
-    result = {
-        "average": average,
-        "category": "High" if average > 50 else "Low",
-        "input_size": len(numbers),
+    arr = np.array(numbers)
+    mean = arr.mean()
+    median = np.median(arr)
+    std_dev = arr.std()
+    # Possibly detect outliers
+    outliers = arr[np.abs(arr - mean) > 2 * std_dev]
+
+    return {
+        "mean": mean,
+        "median": median,
+        "std_dev": std_dev,
+        "outliers": outliers.tolist()
     }
-    return result
 
 def visualize_analysis(result, filename="./output/analysis_visualization.png"):
-    # Extract values
-    average = result["average"]
-    category = result["category"]
-    input_size = result["input_size"]
-        
-    # Visualization
-    plt.figure(figsize=(8, 5))
-    
-    # Bar chart for numeric values
-    metrics = ["Average", "Input Size"]
-    values = [average, input_size]
-    colors = ["blue", "green"]
-    
-    plt.bar(metrics, values, color=colors, alpha=0.7)
-    
-    # Add titles and labels
-    plt.title(f"Data Analysis Visualization(METACALL)\nCategory: {category}", fontsize=14, pad=15)
-    plt.xlabel("Metrics", fontsize=12)
-    plt.ylabel("Values", fontsize=12)
-    
-    # Add value labels on top of bars
-    for i, value in enumerate(values):
-        plt.text(i, value + 1, f"{value:.2f}", ha="center", va="bottom", fontsize=10)
-    
-    # Grid for better readability
-    plt.grid(axis="y", linestyle="--", alpha=0.7)
-    
-    # Save the plot to a file
+    mean = result["mean"]
+    std_dev = result["std_dev"]
+    outliers = result["outliers"]
+
+    fig, ax = plt.subplots(2, 1, figsize=(8, 8))
+
+    # Top subplot: bar chart
+    metrics = ["Mean", "Standard Deviation"]
+    values = [mean, std_dev]
+    ax[0].bar(metrics, values, color=["blue", "red"])
+    ax[0].set_title("Basic Statistics", fontsize=14)
+
+    # Bottom subplot: outliers
+    ax[1].bar(range(len(outliers)), outliers, color="orange")
+    ax[1].set_title("Detected Outliers", fontsize=14)
+
     plt.tight_layout()
     plt.savefig(filename, dpi=300)
     plt.close()
-    print(f"Visualization saved as {filename}")    
-
+    print(f"Visualization saved as {filename}")
 
 def process_message(message):
     try:

index.js

@@ -16,7 +16,7 @@ app.use(express.json());
 app.use(express.urlencoded({ extended: false }));
 
 const server = app.listen(port, () =>
-    console.log(`ws server is listening on http://localhost:${port}`)
+    console.log(`ws server is listening on ws://localhost:${port}`)
 );
 
 const wss = new WebSocketServer({ server });