skcycling.metrics
.training_load_score¶
-
skcycling.metrics.
training_load_score
(activity_power, mpa)[source][source]¶ Training load score.
Grappe et al. proposes to compute the load of an activity by a weighted sum of the time spend in the different ESIE zones.
Read more in the User Guide.
Parameters: - activity_power : Series
A Series containing the power data from an activity.
- mpa : float
Maximum power aerobic. Use
metrics.ftp2mpa
if you use the functional threshold power metric.
Returns: - tls_score: float
Training load score.
References
[1] Grappe, F. “Cyclisme et optimisation de la performance: science et méthodologie de l’entraînement.” De Boeck Supérieur, 2009. Examples
>>> from skcycling.datasets import load_fit >>> from skcycling.io import bikeread >>> from skcycling.metrics import training_load_score >>> ride = bikeread(load_fit()[0]) >>> mpa = 400 >>> tl_score = training_load_score(ride['power'], mpa) >>> print('Training load score {:.2f}'.format(tl_score)) Training load score 74.90