Files
claude-scientific-skills/scientific-skills/timesfm-forecasting/examples/global-temperature/temperature_anomaly.csv
Clayton Young c7c5bc21ff feat(example): add working TimesFM forecast example with global temperature data
- Add NOAA GISTEMP global temperature anomaly dataset (36 months, 2022-2024)
- Run TimesFM 1.0 PyTorch forecast for 2025 (12-month horizon)
- Generate fan chart visualization with 80%/90% confidence intervals
- Create comprehensive markdown report with findings and API notes

API Discovery:
- TimesFM 2.5 PyTorch checkpoint has file format issue (model.safetensors
  vs expected torch_model.ckpt)
- Working API uses TimesFmHparams + TimesFmCheckpoint + TimesFm() constructor
- Documented API in GitHub README differs from actual pip package

Includes:
- temperature_anomaly.csv (input data)
- forecast_output.csv (point forecast + quantiles)
- forecast_output.json (machine-readable output)
- forecast_visualization.png (LFS-tracked)
- run_forecast.py (reusable script)
- visualize_forecast.py (chart generation)
- run_example.sh (one-click runner)
- README.md (full report with findings)
2026-02-23 07:43:04 -05:00

38 lines
591 B
CSV

date,anomaly_c
2022-01-01,0.89
2022-02-01,0.89
2022-03-01,1.02
2022-04-01,0.88
2022-05-01,0.85
2022-06-01,0.88
2022-07-01,0.88
2022-08-01,0.90
2022-09-01,0.88
2022-10-01,0.95
2022-11-01,0.77
2022-12-01,0.78
2023-01-01,0.87
2023-02-01,0.98
2023-03-01,1.21
2023-04-01,1.00
2023-05-01,0.94
2023-06-01,1.08
2023-07-01,1.18
2023-08-01,1.24
2023-09-01,1.47
2023-10-01,1.32
2023-11-01,1.18
2023-12-01,1.16
2024-01-01,1.22
2024-02-01,1.35
2024-03-01,1.34
2024-04-01,1.26
2024-05-01,1.15
2024-06-01,1.20
2024-07-01,1.24
2024-08-01,1.30
2024-09-01,1.28
2024-10-01,1.27
2024-11-01,1.22
2024-12-01,1.20