Update app.py

app.py

@@ -197,19 +197,20 @@ def load_data():
 
 df = load_data()
 
+# ================= HEADER — FIX FINAL (LOGO PASTI MUNCUL) =================
 # ================= HEADER — FIX FINAL (LOGO PASTI MUNCUL) =================
 with st.container():
     col1, col2, col3 = st.columns([1.2, 6, 1.2])
 
     # LEFT — Michelin Logo
     with col1:
-        if os.path.isfile("logo.png"):
-            st.image("logo.png", use_container_width=True)
+        if os.path.exists("logo.png"):
+            try:
+                st.image("logo.png", use_container_width=True)
+            except Exception as e:
+                st.markdown("<h4 style='color:#003A8F; text-align:center;'>Michelin</h4>", unsafe_allow_html=True)
         else:
-            st.markdown(
-                "<h4 style='color:#003A8F; text-align:center;'>Michelin</h4>",
-                unsafe_allow_html=True
-            )
+            st.markdown("<h4 style='color:#003A8F; text-align:center;'>Michelin</h4>", unsafe_allow_html=True)
 
     # CENTER — Title
     with col2:
@@ -226,14 +227,13 @@ with st.container():
 
     # RIGHT — BTech Logo
     with col3:
-        if os.path.isfile("btech.png"):
-            st.image("btech.png", use_container_width=True)
+        if os.path.exists("btech.png"):
+            try:
+                st.image("btech.png", use_container_width=True)
+            except Exception as e:
+                st.markdown("<h4 style='color:#7d7d7d; text-align:center;'>BTech</h4>", unsafe_allow_html=True)
         else:
-            st.markdown(
-                "<h4 style='color:#7d7d7d; text-align:center;'>BTech</h4>",
-                unsafe_allow_html=True
-            )
-
+            st.markdown("<h4 style='color:#7d7d7d; text-align:center;'>BTech</h4>", unsafe_allow_html=True)
 # # ================= HEADER =================
 # st.markdown("""
 # <div class="main-header" style="text-align:center;">
@@ -248,45 +248,45 @@ with st.container():
 
 # ================= LOGO (Perbaikan: Base64 Embed - Selalu Muncul) =================
 # ================= LOGO (Pakai File Lokal - Selalu Muncul di Pojok Kanan Atas) =================
-import os
-import streamlit as st
-
-# ================= PATH AMAN (WAJIB) =================
-BASE_DIR = os.path.dirname(os.path.abspath(__file__))
+# import os
+# import streamlit as st
 
-LOGO_MICHELIN = os.path.join(BASE_DIR, "logo.png")
-LOGO_BTECH = os.path.join(BASE_DIR, "btech.png")
+# # ================= PATH AMAN (WAJIB) =================
+# BASE_DIR = os.path.dirname(os.path.abspath(__file__))
 
-# ================= HEADER =================
-with st.container():
-    col1, col2, col3 = st.columns([1.5, 6, 1.5])
+# LOGO_MICHELIN = os.path.join(BASE_DIR, "logo.png")
+# LOGO_BTECH = os.path.join(BASE_DIR, "btech.png")
 
-    # LEFT — Michelin Logo
-    with col1:
-        if os.path.exists(LOGO_MICHELIN):
-            st.image(LOGO_MICHELIN, width=140)
-        else:
-            st.markdown("**Michelin**")
-
-    # CENTER — Title
-    with col2:
-        st.markdown("""
-        <div style="text-align:center;">
-            <h1 style="margin:0; color:#154D9C; font-weight:800;">
-                Tyre Pressure Monitoring System (TPMS) Analytics for Mining Equipments
-            </h1>
-            <p style="font-size:12px; color:#7d7d7d; margin-top:6px;">
-                Daily trend insights derived from 13–16 December 2023 data
-            </p>
-        </div>
-        """, unsafe_allow_html=True)
-
-    # RIGHT — BTech Logo
-    with col3:
-        if os.path.exists(LOGO_BTECH):
-            st.image(LOGO_BTECH, width=140)
-        else:
-            st.markdown("**BTech**")
+# # ================= HEADER =================
+# with st.container():
+#     col1, col2, col3 = st.columns([1.5, 6, 1.5])
+
+#     # LEFT — Michelin Logo
+#     with col1:
+#         if os.path.exists(LOGO_MICHELIN):
+#             st.image(LOGO_MICHELIN, width=140)
+#         else:
+#             st.markdown("**Michelin**")
+
+#     # CENTER — Title
+#     with col2:
+#         st.markdown("""
+#         <div style="text-align:center;">
+#             <h1 style="margin:0; color:#154D9C; font-weight:800;">
+#                 Tyre Pressure Monitoring System (TPMS) Analytics for Mining Equipments
+#             </h1>
+#             <p style="font-size:12px; color:#7d7d7d; margin-top:6px;">
+#                 Daily trend insights derived from 13–16 December 2023 data
+#             </p>
+#         </div>
+#         """, unsafe_allow_html=True)
+
+#     # RIGHT — BTech Logo
+#     with col3:
+#         if os.path.exists(LOGO_BTECH):
+#             st.image(LOGO_BTECH, width=140)
+#         else:
+#             st.markdown("**BTech**")
 
 # ================= SIDEBAR FILTERS =================
 with st.sidebar:
@@ -1382,118 +1382,118 @@ import numpy as np
 st.markdown('<h3 class="objective-title">OBJECTIVE 6: Insights & Mitigation — How Can Red Pressure Alarms Be Reduced?</h3>', unsafe_allow_html=True)
 
 # ———————————————————————— DATA PREP (HARD-CODED, NO DEF) —————��——————————————————
-# Cek apakah kolom 'Alarm Type' ada
-has_alarm_type = 'Alarm Type' in dff.columns
-
-# Front tyre stats — fallback ke "—" jika NaN/empty/error
-try:
-    front_pressure_avg = dff[dff['Position'].isin([1, 2])]['Pressure (psi)'].mean()
-    front_temp_avg = dff[dff['Position'].isin([1, 2])]['Temperature (°C)'].mean()
-except Exception:
-    front_pressure_avg = np.nan
-    front_temp_avg = np.nan
-
-front_pressure_avg_str = f"{front_pressure_avg:.1f}" if pd.notna(front_pressure_avg) else "—"
-front_temp_avg_str = f"{front_temp_avg:.1f}" if pd.notna(front_temp_avg) else "—"
-
-# Alarm filtering — hanya Red & Amber, jika 'Alarm Type' tidak ada → anggap 0 alarm
-if has_alarm_type:
-    alarm_mask = dff['Alarm Type'].isin(['Red', 'Amber'])
-    alarm_df = dff[alarm_mask].copy()
-else:
-    alarm_df = dff.iloc[0:0]  # empty DataFrame
-
-hourly_counts = alarm_df['hour'].value_counts().reindex(range(24), fill_value=0) if 'hour' in alarm_df.columns else pd.Series([0]*24, index=range(24))
-total_alarms = hourly_counts.sum()
-
-dominant_hour = None
-dominant_percentage = 0.0
-if total_alarms > 0 and not hourly_counts.empty:
-    dominant_hour = int(hourly_counts.idxmax())
-    dominant_percentage = (hourly_counts[dominant_hour] / total_alarms) * 100
-
-# Zone alarm stats
-if 'Zone' in alarm_df.columns and not alarm_df.empty:
-    zone_counts = alarm_df['Zone'].value_counts()
-    if not zone_counts.empty:
-        top_zone = str(zone_counts.index[0])
-        top_zone_percentage = (zone_counts.iloc[0] / total_alarms) * 100 if total_alarms > 0 else 0.0
-    else:
-        top_zone = "—"
-        top_zone_percentage = 0.0
-else:
-    top_zone = "—"
-    top_zone_percentage = 0.0
-
-# Korelasi — aman tanpa fungsi
-corr_pressure_temp_front = 0.0
-corr_speed_temp_rear = 0.0
-
-try:
-    front_df = dff[dff['Position'].isin([1, 2])]
-    rear_df = dff[dff['Position'].isin([3, 4])]
-
-    # Pressure–temp (front)
-    x1, y1 = front_df['Pressure (psi)'], front_df['Temperature (°C)']
-    valid1 = x1.notna() & y1.notna()
-    if valid1.sum() >= 2:
-        c1 = np.corrcoef(x1[valid1], y1[valid1])[0, 1]
-        corr_pressure_temp_front = c1 if np.isfinite(c1) else 0.0
-
-    # Speed–temp (rear)
-    x2, y2 = rear_df['Speed (km/h)'], rear_df['Temperature (°C)']
-    valid2 = x2.notna() & y2.notna()
-    if valid2.sum() >= 2:
-        c2 = np.corrcoef(x2[valid2], y2[valid2])[0, 1]
-        corr_speed_temp_rear = c2 if np.isfinite(c2) else 0.0
-except Exception:
-    pass  # tetap 0.0 jika error
-
-# Format ±0.xx, hindari -0.00
-corr_pressure_temp_front_str = f"{corr_pressure_temp_front:+.2f}".replace("-0.00", "0.00")
-corr_speed_temp_rear_str = f"{corr_speed_temp_rear:+.2f}".replace("-0.00", "0.00")
-
-# Position 1 alarm count
-pos1_alarm_count = alarm_df[alarm_df['Position'] == 1].shape[0] if 'Position' in alarm_df.columns else 0
-
-# ———————————————————————— INSIGHTS ————————————————————————
-insight_lines = []
-
-# 1. Front tyre avg
-line1 = f"1. Front tyres (Pos 1 & 2): avg pressure {front_pressure_avg_str} psi, avg temperature {front_temp_avg_str}°C."
-if pd.notna(front_pressure_avg) and front_pressure_avg > 115:
-    line1 += " Exceeds ideal inflation range (100–110 psi), indicating over-pressure risk."
-insight_lines.append(line1)
-
-# 2. Dominant hour
-if dominant_hour is not None:
-    insight_lines.append(
-        f"2. Peak Red/Amber alarm concentration at {dominant_hour:02d}:00 ({dominant_percentage:.1f}% of total)."
-    )
-else:
-    insight_lines.append("2. No statistically dominant hourly alarm peak.")
-
-# 3. Correlations
-insight_lines.append(
-    f"3. Front pressure–temperature correlation: r = {corr_pressure_temp_front_str}; "
-    f"Rear speed–temperature correlation: r = {corr_speed_temp_rear_str}."
-)
-
-# 4. Top zone
-if top_zone != "—" and top_zone_percentage >= 10.0:
-    insight_lines.append(
-        f"4. Zone {top_zone} accounts for {top_zone_percentage:.1f}% of alarms — highest-risk location."
-    )
-else:
-    insight_lines.append("4. Alarm distribution appears relatively uniform across zones.")
-
-# 5. Position 1 alarms
-if pos1_alarm_count > 0:
-    insight_lines.append(
-        f"5. Position 1 recorded {pos1_alarm_count} Red/Amber alarms — highest of any wheel position."
-    )
-
-insight_text = "<br>".join(insight_lines)
+# # Cek apakah kolom 'Alarm Type' ada
+# has_alarm_type = 'Alarm Type' in dff.columns
+
+# # Front tyre stats — fallback ke "—" jika NaN/empty/error
+# try:
+#     front_pressure_avg = dff[dff['Position'].isin([1, 2])]['Pressure (psi)'].mean()
+#     front_temp_avg = dff[dff['Position'].isin([1, 2])]['Temperature (°C)'].mean()
+# except Exception:
+#     front_pressure_avg = np.nan
+#     front_temp_avg = np.nan
+
+# front_pressure_avg_str = f"{front_pressure_avg:.1f}" if pd.notna(front_pressure_avg) else "—"
+# front_temp_avg_str = f"{front_temp_avg:.1f}" if pd.notna(front_temp_avg) else "—"
+
+# # Alarm filtering — hanya Red & Amber, jika 'Alarm Type' tidak ada → anggap 0 alarm
+# if has_alarm_type:
+#     alarm_mask = dff['Alarm Type'].isin(['Red', 'Amber'])
+#     alarm_df = dff[alarm_mask].copy()
+# else:
+#     alarm_df = dff.iloc[0:0]  # empty DataFrame
+
+# hourly_counts = alarm_df['hour'].value_counts().reindex(range(24), fill_value=0) if 'hour' in alarm_df.columns else pd.Series([0]*24, index=range(24))
+# total_alarms = hourly_counts.sum()
+
+# dominant_hour = None
+# dominant_percentage = 0.0
+# if total_alarms > 0 and not hourly_counts.empty:
+#     dominant_hour = int(hourly_counts.idxmax())
+#     dominant_percentage = (hourly_counts[dominant_hour] / total_alarms) * 100
+
+# # Zone alarm stats
+# if 'Zone' in alarm_df.columns and not alarm_df.empty:
+#     zone_counts = alarm_df['Zone'].value_counts()
+#     if not zone_counts.empty:
+#         top_zone = str(zone_counts.index[0])
+#         top_zone_percentage = (zone_counts.iloc[0] / total_alarms) * 100 if total_alarms > 0 else 0.0
+#     else:
+#         top_zone = "—"
+#         top_zone_percentage = 0.0
+# else:
+#     top_zone = "—"
+#     top_zone_percentage = 0.0
+
+# # Korelasi — aman tanpa fungsi
+# corr_pressure_temp_front = 0.0
+# corr_speed_temp_rear = 0.0
+
+# try:
+#     front_df = dff[dff['Position'].isin([1, 2])]
+#     rear_df = dff[dff['Position'].isin([3, 4])]
+
+#     # Pressure–temp (front)
+#     x1, y1 = front_df['Pressure (psi)'], front_df['Temperature (°C)']
+#     valid1 = x1.notna() & y1.notna()
+#     if valid1.sum() >= 2:
+#         c1 = np.corrcoef(x1[valid1], y1[valid1])[0, 1]
+#         corr_pressure_temp_front = c1 if np.isfinite(c1) else 0.0
+
+#     # Speed–temp (rear)
+#     x2, y2 = rear_df['Speed (km/h)'], rear_df['Temperature (°C)']
+#     valid2 = x2.notna() & y2.notna()
+#     if valid2.sum() >= 2:
+#         c2 = np.corrcoef(x2[valid2], y2[valid2])[0, 1]
+#         corr_speed_temp_rear = c2 if np.isfinite(c2) else 0.0
+# except Exception:
+#     pass  # tetap 0.0 jika error
+
+# # Format ±0.xx, hindari -0.00
+# corr_pressure_temp_front_str = f"{corr_pressure_temp_front:+.2f}".replace("-0.00", "0.00")
+# corr_speed_temp_rear_str = f"{corr_speed_temp_rear:+.2f}".replace("-0.00", "0.00")
+
+# # Position 1 alarm count
+# pos1_alarm_count = alarm_df[alarm_df['Position'] == 1].shape[0] if 'Position' in alarm_df.columns else 0
+
+# # ———————————————————————— INSIGHTS ————————————————————————
+# insight_lines = []
+
+# # 1. Front tyre avg
+# line1 = f"1. Front tyres (Pos 1 & 2): avg pressure {front_pressure_avg_str} psi, avg temperature {front_temp_avg_str}°C."
+# if pd.notna(front_pressure_avg) and front_pressure_avg > 115:
+#     line1 += " Exceeds ideal inflation range (100–110 psi), indicating over-pressure risk."
+# insight_lines.append(line1)
+
+# # 2. Dominant hour
+# if dominant_hour is not None:
+#     insight_lines.append(
+#         f"2. Peak Red/Amber alarm concentration at {dominant_hour:02d}:00 ({dominant_percentage:.1f}% of total)."
+#     )
+# else:
+#     insight_lines.append("2. No statistically dominant hourly alarm peak.")
+
+# # 3. Correlations
+# insight_lines.append(
+#     f"3. Front pressure–temperature correlation: r = {corr_pressure_temp_front_str}; "
+#     f"Rear speed–temperature correlation: r = {corr_speed_temp_rear_str}."
+# )
+
+# # 4. Top zone
+# if top_zone != "—" and top_zone_percentage >= 10.0:
+#     insight_lines.append(
+#         f"4. Zone {top_zone} accounts for {top_zone_percentage:.1f}% of alarms — highest-risk location."
+#     )
+# else:
+#     insight_lines.append("4. Alarm distribution appears relatively uniform across zones.")
+
+# # 5. Position 1 alarms
+# if pos1_alarm_count > 0:
+#     insight_lines.append(
+#         f"5. Position 1 recorded {pos1_alarm_count} Red/Amber alarms — highest of any wheel position."
+#     )
+
+# insight_text = "<br>".join(insight_lines)
 
 # ———————————————————————— SUMMARY (HARD-CODED) ————————————————————————
 summary_text = """\
@@ -1512,14 +1512,14 @@ recommendation_text = """\
 """
 
 # ———————————————————————— RENDER ————————————————————————
-st.markdown('<h4 style="text-align:center; margin:10px 0 5px 0; font-weight:bold;">INSIGHTS</h4>', unsafe_allow_html=True)
-st.markdown(f"""
-<div class="insight-box">
-    <div class="content" style="text-align:left;">
-{insight_text}
-    </div>
-</div>
-""", unsafe_allow_html=True)
+# st.markdown('<h4 style="text-align:center; margin:10px 0 5px 0; font-weight:bold;">INSIGHTS</h4>', unsafe_allow_html=True)
+# st.markdown(f"""
+# <div class="insight-box">
+#     <div class="content" style="text-align:left;">
+# {insight_text}
+#     </div>
+# </div>
+# """, unsafe_allow_html=True)
 
 st.markdown('<h4 style="text-align:center; margin:15px 0 5px 0; font-weight:bold;">SUMMARY</h4>', unsafe_allow_html=True)
 st.markdown(f"""