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⚠ Anomalies use the Tukey IQR method:
values outside Q1 − 2×IQR or Q3 + 2×IQR
on the visible data window.
🌬 Wind Rose
⏱ Daily Pattern
🏆 Records
🏠 Thermal
×
▶ ⚙ Configuration
🔥 Heating Active
❄ Cooling Active
🌿 Passive Periods
All dates not in a heating or cooling range.
These train the regression model.
🏠 Indoor Temperature Sensors
Each one is modelled against the outdoor sensor separately.
🌤 Outdoor Temperature Sensor
The reference every indoor sensor is compared against. A sensor used here can't also be an indoor sensor.
🌀 HVAC Temperature Sensor
A probe in the supply duct. When present it measures when heating and cooling actually ran, and the model uses that instead of the season ranges above.
Thermal Phase: outdoor (lagged) vs indoor °F ℹ
Thermal Phase Scatter
Outdoor temp (shifted by thermal lag) vs indoor temp at that moment.

How to read it:
• X-axis — outdoor °F, smoothed & shifted back by the lag hours
• Y-axis — indoor °F at that moment
• Dashed line — regression fit: what indoor temp should be from outdoor alone
• ■ Orange — heater running (indoor warmer than predicted)
• ■ Blue — A/C running (indoor cooler than predicted)
• ■ Gray — HVAC idle, house tracking outdoor naturally

The physics:
• Tight cluster along line = good coupling, HVAC off
• Slope = thermal coupling (indoor °F per outdoor °F)
• Wide scatter = heavy HVAC use fighting the outdoor temp
• Flat line = thermally decoupled (typical for basements)
Series
High
Date
Low
Date

Ignore periods

Every series uses all of its data by default. Set a bound here to hide readings you know are wrong — a new sensor still equilibrating, or a stretch where one misbehaved. Ignore before keeps the reading at that exact time; ignore after hides everything past it. Times are your local clock, the same one the chart is drawn in. Nothing is deleted — clear a bound and the readings come back. These rules are saved in this browser only, and apply to whatever data you load.