MetricsΒΆ
The rainymotion library provides the extensive list of goodness-of-fit statistical metrics to evaluate nowcasting models performance.
| Metric | Description |
|---|---|
| Regression | |
| R | Correlation coefficient |
| R2 | Coefficient of determination |
| RMSE | Root mean squared error |
| MAE | Mean absolute error |
| QPN specific | |
| CSI | Critical Success Index |
| FAR | False Alarm Rate |
| POD | Probability Of Detection |
| HSS | Heidke Skill Score |
| ETS | Equitable Threat Score |
| BSS | Brier Skill Score |
| ML specific | |
| ACC | Accuracy |
| precision | Precision |
| recall | Recall |
| FSC | F1-score |
| MCC | Matthews Correlation Coefficient |
You can easily use any metric for verification of your nowcasts:
# import the specific metric from the rainymotion library
from rainymotion.metrics import CSI
# read your observations and simulations
obs = np.load("/path/to/observations")
sim = np.load("/path/to/simulations")
# calculate the corresponding metric
csi = CSI(obs, sim, threshold=1.0)
See also