README.md

metadata

title: Transformer Oil Temperature Forecaster
emoji: ⚡
colorFrom: red
colorTo: blue
sdk: gradio
sdk_version: 6.12.0
app_file: app.py
pinned: false

⚡ Transformer Oil Temperature Forecaster

ARIMAX · Anomaly Detection · Time Series Analysis

Upload ETT-style transformer CSV data and get:

Feature	Details
Model	ARIMAX — auto-selects best (p, d, q) via AIC grid search
Endog	OT — oil temperature
Exog	HUFL, HULL, MUFL, MULL, LUFL, LULL — load features
Stationarity	ADF test; auto-applies 1st differencing if needed
Anomaly Detection	Residual-based, threshold = mean ± 2.5σ
Evaluation	MAE + RMSE on 20% hold-out set

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📂 Expected CSV Format

date,HUFL,HULL,MUFL,MULL,LUFL,LULL,OT
2016-07-01 00:00:00,5.827,2.009,1.599,0.462,4.203,1.340,30.531
...

The ETT (Electricity Transformer Temperature) dataset works out of the box.
Download it from: https://github.com/zhouhaoyi/ETDataset

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🚀 Running Locally

pip install -r requirements.txt
python app.py

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📐 Architecture

CSV Upload
    │
    ▼
load_data()          ← parse datetime index, ffill missing
    │
    ▼
check_stationarity() ← ADF test → d value
    │
    ▼
train_arimax()       ← grid search (p,q) on 80% train split
    │
    ├──► forecast()          ← out-of-sample N steps
    │
    └──► detect_anomalies()  ← residual threshold flagging