Updated UI and Excel Function

app.py

@@ -3,26 +3,27 @@ import pandas as pd
 import matplotlib.pyplot as plt
 import numpy as np
 import io
+import os
 
 app = Flask(__name__)
 
-# Global data cache
+# Cache
 data_cache = {
-    "df1": None,       # Golden data
+    "df1": None,
     "limits": {},
     "cols": [],
-    "golden_loaded": False
+    "golden_loaded": False,
+    "comparison_file": None
 }
 
 
 def process_golden_file(golden_file):
-    """Load and store Golden Excel data + limits."""
+    """Load Golden data and extract limits."""
     limits_df1 = pd.read_excel(golden_file, nrows=4)
     df1 = pd.read_excel(golden_file)
     df1 = df1.drop([0, 1, 2, 3])
     df1 = df1.apply(pd.to_numeric, errors="coerce")
 
-    # Extract limits
     limits_df1 = limits_df1.drop([0])
     ignore_cols = ["SITE_NUM", "PART_ID", "PASSFG", "SOFT_BIN", "T_TIME", "TEST_NUM"]
     cols_to_plot = [col for col in limits_df1.columns if "_" in col and col not in ignore_cols]
@@ -33,53 +34,73 @@ def process_golden_file(golden_file):
         for col in limits_df1.columns
     }
 
-    # Store globally
-    data_cache["df1"] = df1
-    data_cache["limits"] = limits
-    data_cache["cols"] = cols_to_plot
-    data_cache["golden_loaded"] = True
+    data_cache.update({
+        "df1": df1,
+        "limits": limits,
+        "cols": cols_to_plot,
+        "golden_loaded": True
+    })
 
 
 def process_test_file(test_file):
-    """Load and return the Test Excel data."""
+    """Load Test data."""
     df2 = pd.read_excel(test_file)
     df2 = df2.drop([0, 1, 2, 3])
     df2 = df2.apply(pd.to_numeric, errors="coerce")
     return df2
 
 
+def generate_comparison_excel(df2):
+    """Generate comparison Excel (mean, std, min, max for both)."""
+    df1 = data_cache["df1"]
+    common_cols = [c for c in df1.columns if c in df2.columns]
+
+    summary = []
+    for col in common_cols:
+        g_mean, t_mean = df1[col].mean(), df2[col].mean()
+        g_std, t_std = df1[col].std(), df2[col].std()
+        g_min, t_min = df1[col].min(), df2[col].min()
+        g_max, t_max = df1[col].max(), df2[col].max()
+
+        diff = t_mean - g_mean if pd.notna(t_mean) and pd.notna(g_mean) else np.nan
+        summary.append([col, g_mean, t_mean, diff, g_std, t_std, g_min, t_min, g_max, t_max])
+
+    comp_df = pd.DataFrame(summary, columns=[
+        "Parameter", "Golden_Mean", "Test_Mean", "Mean_Diff",
+        "Golden_Std", "Test_Std", "Golden_Min", "Test_Min", "Golden_Max", "Test_Max"
+    ])
+
+    path = "comparison_result.xlsx"
+    comp_df.to_excel(path, index=False)
+    data_cache["comparison_file"] = path
+
+
 def generate_plot(df2, col):
-    """Generate plot comparing Golden and Test for a specific column."""
+    """Generate and return a plot comparing Golden vs Test."""
     df1, limits = data_cache["df1"], data_cache["limits"]
 
     plt.figure(figsize=(6, 4))
-
-    # Golden
     x1 = np.arange(1, len(df1[col]) + 1)
-    y1 = pd.to_numeric(df1[col], errors="coerce").values
-    plt.plot(x1, y1, marker="o", linestyle="-", color="blue", label="Golden")
+    plt.plot(x1, df1[col], 'o-', label="Golden", color='blue')
 
-    # Test
     if col in df2.columns:
         x2 = np.arange(1, len(df2[col]) + 1)
-        y2 = pd.to_numeric(df2[col], errors="coerce").values
-        plt.plot(x2, y2, marker="s", linestyle="--", color="red", label="Test")
+        plt.plot(x2, df2[col], 's--', label="Test", color='red')
 
-    # Limits
     if col in limits:
         ll, ul = limits[col]["LL"], limits[col]["UL"]
-        plt.axhline(ll, color="green", linestyle="--", linewidth=2, label="LL")
-        plt.axhline(ul, color="orange", linestyle="--", linewidth=2, label="UL")
+        plt.axhline(ll, color='green', linestyle='--', label='LL')
+        plt.axhline(ul, color='orange', linestyle='--', label='UL')
 
     plt.title(f"{col}")
     plt.xlabel("Part # (sequence)")
     plt.ylabel("Value")
-    plt.grid(True, linestyle="--", alpha=0.7)
-    plt.legend(fontsize="small")
+    plt.legend(fontsize='small')
+    plt.grid(True, linestyle='--', alpha=0.7)
     plt.tight_layout()
 
     buf = io.BytesIO()
-    plt.savefig(buf, format="png", bbox_inches="tight")
+    plt.savefig(buf, format='png', bbox_inches='tight')
     buf.seek(0)
     plt.close()
     return buf
@@ -87,52 +108,59 @@ def generate_plot(df2, col):
 
 @app.route("/", methods=["GET", "POST"])
 def index():
-    """Handle golden upload (if not loaded) or test upload (if golden loaded)."""
     if request.method == "POST":
+        # Upload Golden first
         if not data_cache["golden_loaded"]:
-            # Upload Golden
             golden_file = request.files.get("golden_file")
             if not golden_file:
-                return render_template("index.html", error="Please upload a Golden file first.")
+                return render_template("index.html", error="Please upload Golden file.")
             try:
                 process_golden_file(golden_file)
-                return render_template("index.html", message="Golden data loaded successfully! Now upload Test data.")
+                return render_template("index.html", message="Golden data loaded successfully!")
             except Exception as e:
                 return render_template("index.html", error=f"Error loading Golden file: {e}")
+
+        # Upload Test data next
         else:
-            # Upload Test
             test_file = request.files.get("test_file")
             if not test_file:
-                return render_template("index.html", error="Please upload a Test file.")
+                return render_template("index.html", error="Please upload Test data.")
             try:
                 df2 = process_test_file(test_file)
-                cols = data_cache["cols"]
-                preview_cols = cols[:3] if len(cols) >= 3 else cols
-                # Store test temporarily in memory (for this view only)
                 data_cache["df2_temp"] = df2
-                return render_template("plot.html", cols=cols, preview_cols=preview_cols)
+                generate_comparison_excel(df2)
+                return render_template(
+                    "plot.html",
+                    cols=data_cache["cols"],
+                    file_ready=True
+                )
             except Exception as e:
-                return render_template("index.html", error=f"Error loading Test file: {e}")
+                return render_template("index.html", error=f"Error processing Test file: {e}")
 
     return render_template("index.html", golden_loaded=data_cache["golden_loaded"])
 
 
 @app.route("/plot_image/<col>")
 def plot_image(col):
-    """Generate plot image for selected column."""
     df2 = data_cache.get("df2_temp")
     if df2 is None:
-        return "No Test data uploaded yet."
-    try:
-        buf = generate_plot(df2, col)
-        return send_file(buf, mimetype="image/png")
-    except Exception as e:
-        return f"Error generating plot: {str(e)}"
+        return "No Test data loaded."
+    buf = generate_plot(df2, col)
+    return send_file(buf, mimetype="image/png")
+
+
+@app.route("/download_comparison")
+def download_comparison():
+    """Download comparison Excel file."""
+    path = data_cache.get("comparison_file")
+    if path and os.path.exists(path):
+        return send_file(path, as_attachment=True)
+    return "No comparison file available."
 
 
 @app.route("/reset_golden")
 def reset_golden():
-    """Clear the Golden file from memory."""
+    """Reset golden data."""
     data_cache.update({"df1": None, "limits": {}, "cols": [], "golden_loaded": False})
     return redirect(url_for("index"))
 

templates/plot.html

@@ -1,70 +1,87 @@
 <!DOCTYPE html>
-<html lang="en">
+<html>
 <head>
-    <meta charset="UTF-8">
-    <title>IPM Data Plots</title>
-    <link href="https://cdn.jsdelivr.net/npm/bootstrap@5.3.3/dist/css/bootstrap.min.css" rel="stylesheet">
-    <style>
-        body {
-            background: #f6f8fa;
-            font-family: "Segoe UI", Arial, sans-serif;
-            padding: 30px;
-        }
-        h2 {
-            text-align: center;
-            margin-bottom: 30px;
-        }
-        img {
-            max-width: 90%;
-            border-radius: 10px;
-            box-shadow: 0 3px 12px rgba(0,0,0,0.1);
-            margin: 20px auto;
-            display: block;
-        }
-        .dropdown-container {
-            text-align: center;
-            margin-top: 20px;
-        }
-        select {
-            width: 60%;
-            padding: 10px;
-            border-radius: 6px;
-            border: 1px solid #ccc;
-        }
-        .card {
-            border: none;
-            border-radius: 12px;
-            box-shadow: 0 3px 12px rgba(0,0,0,0.08);
-            background: #fff;
-            padding: 20px;
-            margin-bottom: 25px;
-        }
-        .preview-title {
-            font-weight: 600;
-            margin-top: 10px;
-        }
-    </style>
-    <script>
-        function showPlot() {
-            const col = document.getElementById("col-select").value;
-            document.getElementById("dynamic-plot").src = "/plot_image/" + encodeURIComponent(col);
-        }
-    </script>
+  <title>IPM Comparison</title>
+  <style>
+    body {
+      font-family: 'Segoe UI', sans-serif;
+      background: #f7f9fc;
+      text-align: center;
+      padding: 30px;
+    }
+    h2 {
+      color: #1e88e5;
+    }
+    select {
+      padding: 10px;
+      margin: 20px;
+      border-radius: 6px;
+      border: 1px solid #aaa;
+      font-size: 16px;
+    }
+    img {
+      max-width: 90%;
+      border: 1px solid #ddd;
+      border-radius: 8px;
+      margin-top: 20px;
+    }
+    a {
+      display: inline-block;
+      background-color: #43a047;
+      color: white;
+      padding: 10px 20px;
+      text-decoration: none;
+      border-radius: 6px;
+      margin-top: 15px;
+      transition: background 0.3s ease;
+    }
+    a:hover {
+      background-color: #2e7d32;
+    }
+    button {
+      background-color: #e53935;
+      color: white;
+      border: none;
+      padding: 10px 20px;
+      border-radius: 6px;
+      margin-top: 20px;
+      cursor: pointer;
+    }
+    button:hover {
+      background-color: #c62828;
+    }
+  </style>
+
+  <script>
+    function showPlot() {
+      const col = document.getElementById("col-select").value;
+      document.getElementById("plot-img").src = "/plot_image/" + encodeURIComponent(col);
+    }
+  </script>
 </head>
 <body>
-    <div class="container">
-        <h2>📈 Golden vs Test Comparison</h2>
 
-        <div class="card">
-            <h4>Preview (First few plots)</h4>
-            {% for c in preview_cols %}
-                <div class="preview-title">{{ c }}</div>
-                <img src="/plot_image/{{ c }}" alt="{{ c }}">
-            {% endfor %}
-        </div>
+  <h2>📊 Golden vs Test Data Comparison</h2>
+
+  {% if file_ready %}
+  <a href="/download_comparison">⬇️ Download Comparison Excel</a>
+  {% endif %}
+
+  <h3>Select Parameter to Plot:</h3>
+  <select id="col-select" onchange="showPlot()">
+    <option disabled selected>Select a column</option>
+    {% for c in cols %}
+    <option value="{{ c }}">{{ c }}</option>
+    {% endfor %}
+  </select>
+
+  <br>
+  <img id="plot-img" src="" alt="Plot will appear here">
+
+  <br>
+  <form action="/reset_golden">
+    <button>Reset Golden Data</button>
+  </form>
 
-        <div class="card">
-            <h4>Select Another Column to View</h4>
-            <div class="dropdown-container">
-                <select id="col-select" onchange="showPlot()">
-                    <option
+</body>
+</html>