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Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
@@ -28,17 +28,16 @@ def simulate_pole(pole_id, site_name):
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total_power = solar_kwh + wind_kwh
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power_status = 'Sufficient' if total_power >= power_required else 'Insufficient'
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tilt_angle = round(random.uniform(0, 45), 2)
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vibration = round(random.uniform(0, 5), 2)
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camera_status = random.choice(['Online', 'Offline'])
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alert_level = 'Green'
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if
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alert_level = 'Yellow'
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if
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alert_level = 'Red'
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health_score = max(0, 100 - (
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timestamp = datetime.now() - timedelta(hours=random.randint(0, 6))
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return {
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@@ -51,7 +50,6 @@ def simulate_pole(pole_id, site_name):
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'Power Required (kWh)': power_required,
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'Total Power (kWh)': total_power,
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'Power Status': power_status,
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'Tilt Angle (Β°)': tilt_angle,
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'Vibration (g)': vibration,
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'Camera Status': camera_status,
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'Health Score': round(health_score, 2),
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@@ -86,12 +84,33 @@ if selected_site in SITES:
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filtered_df = site_df[(site_df['Alert Level'].isin(alert_filter)) & (site_df['Camera Status'].isin(camera_filter))]
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st.dataframe(filtered_df, use_container_width=True)
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# Map showing all poles by alert level color
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st.subheader("π All Pole Locations with Alert Levels")
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total_power = solar_kwh + wind_kwh
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power_status = 'Sufficient' if total_power >= power_required else 'Insufficient'
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vibration = round(random.uniform(0, 5), 2)
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camera_status = random.choice(['Online', 'Offline'])
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alert_level = 'Green'
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if vibration > 3:
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alert_level = 'Yellow'
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if vibration > 4.5:
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alert_level = 'Red'
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health_score = max(0, 100 - ( vibration * 10))
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timestamp = datetime.now() - timedelta(hours=random.randint(0, 6))
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return {
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'Power Required (kWh)': power_required,
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'Total Power (kWh)': total_power,
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'Power Status': power_status,
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'Vibration (g)': vibration,
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'Camera Status': camera_status,
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'Health Score': round(health_score, 2),
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filtered_df = site_df[(site_df['Alert Level'].isin(alert_filter)) & (site_df['Camera Status'].isin(camera_filter))]
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st.dataframe(filtered_df, use_container_width=True)
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st.subheader("π Energy Generation per Pole")
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# Reshape the data for comparison: one row per Pole ID and energy source
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energy_long_df = site_df[['Pole ID', 'Solar (kWh)', 'Wind (kWh)']].melt(
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id_vars='Pole ID',
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value_vars=['Solar (kWh)', 'Wind (kWh)'],
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var_name='Energy Source',
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value_name='kWh'
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)
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# Plot a grouped bar chart using Altair
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import altair as alt
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bar_chart = alt.Chart(energy_long_df).mark_bar().encode(
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x=alt.X('Pole ID:N', sort=None, title='Pole ID'),
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y=alt.Y('kWh:Q'),
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color='Energy Source:N',
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tooltip=['Pole ID', 'Energy Source', 'kWh']
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).properties(
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width=800,
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height=400
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).configure_axisX(labelAngle=45)
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st.altair_chart(bar_chart, use_container_width=True)
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st.subheader("π Vibration")
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st.scatter_chart(site_df[[ 'Vibration (g)']])
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# Map showing all poles by alert level color
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st.subheader("π All Pole Locations with Alert Levels")
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