scikit-cycling API¶
This is the full API documentation of scikit-cycling
Extraction¶
The skcycling.extraction module includes algorithms to extract
information from cycling data.
extraction.activity_power_profile(activity) |
Compute the power profile for an activity. |
extraction.acceleration(activity[, periods, …]) |
Compute the acceleration (i.e. |
extraction.gradient_activity(activity[, …]) |
Compute the gradient for all given columns. |
extraction.gradient_elevation(activity[, …]) |
Compute the elevation gradient. |
extraction.gradient_heart_rate(activity[, …]) |
Compute the heart-rate gradient. |
Extraction¶
The skcycling.metrics module include score functions.
Single cycling activity¶
metrics.normalized_power_score(…[, …]) |
Normalized power®. |
metrics.intensity_factor_score(…) |
Intensity factor®. |
metrics.training_stress_score(…) |
Training stress score®. |
metrics.training_load_score(activity_power, mpa) |
Training load score. |
Power-profile¶
metrics.aerobic_meta_model(record_power_profile) |
Compute the aerobic metabolism model from the record power-profile. |
Models¶
The skcycling.model module includes algorithms to model cycling data.
Power¶
model.strava_power_model(activity, …[, …]) |
Strava model used to estimate power. |
Utilities¶
The skcycling.utils module include utility functions.
utils.validate_filenames(filenames) |
Check the filenames and expand in the case of wildcard. |
IO interaction¶
The skcycling.io module includes utility to load data.
io.bikeread(filename[, drop_nan]) |
Read power data file. |
Datasets¶
The skcycling.datasets module includes utilities to load datasets.
datasets.load_fit([returned_type, set_data]) |
Return path to some FIT toy data. |
datasets.load_rider() |
Return the path to a CSV file containing rider information. |