request-to-get-code

.gitignore

@@ -1,7 +1,4 @@
 data/
-*.ipynb
+test.ipynb
 *.csv
-*.xlsx
-*.json
-charts/*.png
-charts_compare/*.png
+*.xlsx

README.md

@@ -12,13 +12,3 @@ short_description: This space is created to compare the test data
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
-
-<h1>Added new SPC system</h1>
-<h2>To check this out in your local environment</h2>
-
-<ul>
-    <li>Keep the input file in the same folder</li>
-    <li>Key in the input file in the terminal</li>
-    <li>Run the <code>spc_engine.py</code></li>
-    <li>This will generate all the graphs inside the <code>charts</code> folder</li>
-</ul>

SPC_System/spc_engine.py

@@ -1,122 +0,0 @@
-import pandas as pd
-import matplotlib.pyplot as plt
-import numpy as np
-import os
-
-# --------- Load three datasets ----------
-df_t1 = pd.read_excel("tester#1.xlsx")
-df_t2 = pd.read_excel("tester#2.xlsx")
-df_gold = pd.read_excel("Golden_Data.xlsx")
-
-# --------- Get parameter list ----------
-df_new = df_gold.head(3).dropna(axis=1, how="all")
-df_param = df_new.drop(["T_TIME", "SITE_NUM"], axis=1)
-parameters = list(df_param.columns)
-
-# --------- Build master dictionary ----------
-data = {
-    param: {
-        "Tester1": pd.to_numeric(df_t1[param].iloc[3:], errors="coerce").dropna().tolist(),
-        "Tester2": pd.to_numeric(df_t2[param].iloc[3:], errors="coerce").dropna().tolist(),
-        "Golden":  pd.to_numeric(df_gold[param].iloc[3:], errors="coerce").dropna().tolist(),
-        "LimitL": df_new[param].iloc[1],
-        "LimitU": df_new[param].iloc[2],
-        "Unit": df_new[param].iloc[0]
-    }
-    for param in parameters
-}
-
-# --------- Plot comparison SPC ----------
-os.makedirs("./charts_compare", exist_ok=True)
-
-for param in parameters:
-
-    t1 = np.array(data[param]["Tester1"])
-    t2 = np.array(data[param]["Tester2"])
-    gold = np.array(data[param]["Golden"])
-
-    limit_l = data[param]["LimitL"]
-    limit_u = data[param]["LimitU"]
-    unit = data[param]["Unit"]
-
-    # Golden reference control band
-    mean = gold.mean()
-    t1_mean = t1.mean()
-    t2_mean = t2.mean()
-    std = gold.std(ddof=1)
-    UCL = mean + 3 * std
-    LCL = mean - 3 * std
-
-    # ---- Fix max length ----
-    max_len = max(len(t1), len(t2), len(gold))
-    xaxis = np.arange(1, max_len + 1)
-
-    # ---- Correlation ----
-    min_len_t1 = min(len(t1), len(gold))
-    min_len_t2 = min(len(t2), len(gold))
-
-    corr_t1 = np.corrcoef(t1[:min_len_t1], gold[:min_len_t1])[0,1]
-    corr_t2 = np.corrcoef(t2[:min_len_t2], gold[:min_len_t2])[0,1]
-    corr_t1_t2 = np.corrcoef(t1[:min_len_t1], t2[:min_len_t2])[0,1]
-
-    # ---- CPK (based on Golden dataset) ----
-    cpk = min((mean - limit_l) / (3 * std), (limit_u - mean) / (3 * std))
-
-    plt.figure(figsize=(10,6))
-
-    # --- Plot all datasets ---
-    plt.plot(range(1, len(t1)+1), t1, marker='o', label="Tester #1")
-    plt.plot(range(1, len(t2)+1), t2, marker='o', label="Tester #2")
-    plt.plot(range(1, len(gold)+1), gold, marker='o', label="Gold Reference", linewidth=3)
-
-    # --- SPC lines ---
-    plt.axhline(mean, linestyle='--', color='black', label=f"Mean (Gold)")
-    plt.axhline(UCL, linestyle='-.', color='red', label="UCL (Mean + 3σ)")
-    plt.axhline(LCL, linestyle='-.', color='red', label="LCL (Mean – 3σ)")
-
-    # --- Spec Limits ---
-    plt.axhline(limit_l, linestyle=':', color='orange', label="Lower Spec")
-    plt.axhline(limit_u, linestyle=':', color='orange', label="Upper Spec")
-
-    # ---- Fix X-axis ----
-    # plt.xticks(np.arange(1, max_len + 1, step=1))
-    # plt.xlim(1, max_len)
-
-    # ---- Fix X-axis with whole numbers + padding ----
-    max_len = max(len(t1), len(t2), len(gold))
-
-    plt.xticks(np.arange(1, max_len + 1, 1))  # whole numbers
-    plt.xlim(0, max_len + 1)  # space before 1 and after last point
-
-
-    # ---- Add CPK + Correlation text box ----
-    textstr = (
-        f"Gold Mean = {mean:.4f}\n"
-        f"Std Dev = {std:.4f}\n"
-        f"CPK = {cpk:.4f}\n"
-        f"Corr T1–Gold = {corr_t1:.4f}\n"
-        f"Corr T2–Gold = {corr_t2:.4f}\n"
-        f"Corr T1-T2 = {corr_t1_t2:.4f}\n"
-        f"Tester#1 Mean = {t1_mean:.4f}\n"
-        f"Tester#2 Mean = {t2_mean:4f}\n"
-    )
-
-    plt.gca().text(
-        0.02, 0.98, textstr,
-        transform=plt.gca().transAxes,
-        fontsize=10,
-        verticalalignment='top',
-        bbox=dict(boxstyle="round,pad=0.4", facecolor="white", alpha=0.8)
-    )
-
-    # Labels
-    plt.title(f"SPC Comparison - {param} ({unit})")
-    plt.xlabel("Sample Index")
-    plt.ylabel(f"Value ({unit})")
-    plt.grid(True)
-    plt.legend()
-    plt.tight_layout()
-
-    # Save chart
-    plt.savefig(f"./charts_compare/SPC_compare_{param}.png", dpi=300)
-    plt.close()