Test

app.py

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+import gradio as gr
+import pandas as pd
+import matplotlib.pyplot as plt
+import numpy as np
+import io
+
+def plot_excel_data(golden_data_file, manipulated_data_file):
+    """
+    Reads two Excel files, plots the time-series data, and adds spec limits.
+    """
+    if golden_data_file is None:
+        raise gr.Error("Please upload the 'Golden Data' Excel file.")
+
+    try:
+        # Read first 3 rows to extract limits from the golden data
+        limits_df1 = pd.read_excel(golden_data_file.name, nrows=4)
+        limits_df1 = limits_df1.drop(0)
+
+        # Data (skip first 3 rows)
+        df1 = pd.read_excel(golden_data_file.name)
+        df1 = df1.drop([0, 1, 2, 3])
+        df1 = df1.apply(pd.to_numeric, errors="coerce")
+    except Exception as e:
+        raise gr.Error(f"Error processing 'Golden Data' file: {e}")
+
+    # Build limits dictionary per column
+    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]
+    limits_df1 = limits_df1.drop(columns=ignore_cols)
+    limits = {
+        col: {"LL": limits_df1.iloc[0][col], "UL": limits_df1.iloc[1][col]}
+        for col in limits_df1.columns
+    }
+
+    # Initialize a second dataframe if a file is provided
+    df2 = None
+    if manipulated_data_file is not None:
+        try:
+            df2 = pd.read_excel(manipulated_data_file.name)
+            df2 = df2.drop([0, 1, 2, 3])
+            df2 = df2.apply(pd.to_numeric, errors="coerce")
+        except Exception as e:
+            raise gr.Error(f"Error processing 'Manipulated Data' file: {e}")
+
+    # Plotting logic
+    n_cols = 3
+    n_rows = (len(df1.columns) + n_cols - 1) // n_cols
+
+    fig, axes = plt.subplots(n_rows, n_cols, figsize=(n_cols * 5, n_rows * 3.5))
+    if n_rows * n_cols > len(df1.columns):
+        # Flatten axes array for easy iteration, then turn off unused subplots
+        for i in range(len(df1.columns), n_rows * n_cols):
+            axes.flatten()[i].axis('off')
+    
+    for i, col in enumerate(cols_to_plot):
+        ax = axes.flatten()[i] if n_rows > 1 else axes[i]
+        
+        # Golden data (Old)
+        x1 = np.arange(1, len(df1[col]) + 1)
+        y1 = pd.to_numeric(df1[col], errors="coerce").values
+        ax.plot(x1, y1, marker="o", linestyle="-", color="blue", label="Old")
+
+        # New data (if provided)
+        if df2 is not None and col in df2.columns:
+            x2 = np.arange(1, len(df2[col]) + 1)
+            y2 = pd.to_numeric(df2[col], errors="coerce").values
+            ax.plot(x2, y2, marker="s", linestyle="--", color="red", label="New")
+
+        # Spec limits
+        if col in limits:
+            ll, ul = limits[col]["LL"], limits[col]["UL"]
+            ax.axhline(ll, color="green", linestyle="--", linewidth=2, label="LL")
+            ax.axhline(ul, color="orange", linestyle="--", linewidth=2, label="UL")
+
+        ax.set_title(f"{col}")
+        ax.set_xlabel("Part # (sequence)")
+        ax.set_ylabel("Value")
+        ax.set_xticks(x1)
+        ax.grid(True, linestyle="--", alpha=0.7)
+        ax.legend()
+
+    plt.tight_layout()
+    return fig
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=plot_excel_data,
+    inputs=[
+        gr.File(label="Upload IPM_Golden_Data.xlsx (Required)"),
+        gr.File(label="Upload IPM_Golden_Data_Manipulated.xlsx (Optional)"),
+    ],
+    outputs=gr.Plot(label="Comparison Plots"),
+    title="Time-Series Data Comparison",
+    description="Upload two Excel files to compare time-series data and visualize specification limits. The first file (Golden Data) is required and will be used to extract the limits."
+)
+
+if __name__ == "__main__":
+    iface.launch()

requirement.txt

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+gradio
+pandas
+matplotlib
+numpy
+openpyxl