Bee health data calculation model B-GOOD Work package 5. This code was developed by SESS in Aarhus University with the support of the B-GOOD project: https://b-good-project.eu/.
Calculates a colony survival prediction value for a single hive based on an array of hourly weight data. The input weight data is assumed to be the 'cleaned weight' (beekeeper actions removed from the weight measurements), evenly spaced with 1-hour intervals. Inference is ran on the input data using a pre-trained PyTorch LSTM model (hsi.pt).
- Python3: https://www.python.org/downloads/
- PyTorch: https://download.pytorch.org/whl/torch_stable.html
- Numpy: https://numpy.org/
Replace test_data with array of cleaned weight data
python3 b_good_prediction.py
Xiaodong Duan, [email protected]
- net_weight_kg (weight excluding beekeeper actions)
- 1 hour average
- relative interval of 30 * 24 hours, looking back from now
- data per hive
- float between 0 and 1