cycling stats
v0.1.0
根据心率和功率计计算统计数据，例如在个性化心率和功率区花费的时间、标准化功率、强度因子、训练压力分数、变异指数、效率因子、慢性训练负荷、急性训练负荷和训练压力平衡。
该软件包在 pypi 下可用：
pip install cycling-stats
您可以按如下方式使用该包。一个简单的例子：您可以导入函数training_stress_score ，如下所示。
from cyclingstats . stats import training_stress_score该包要求您将数据保存在pandas.DataFrame中。以下示例说明了您拥有来自多个单独训练课程的时间序列，并且您希望单独计算每天骑行的统计数据。
import pandas as pd
from cyclingstats . stats import calc_hr_zones , calc_power_zones , agg_zones , agg_power
from cyclingstats . stats import chronic_training_load , acute_training_load , training_stress_balance
# read time series of power and/or heart rate
df = pd . read_csv ( "PATH_TO_YOUR_HEARTRATE_AND_POWER_DATA" )
df [ 'date' ] = pd . to_datetime ( df [ 'timestamp' ]. dt . date )
# perform any other preprocessing steps here
# ---------- zones
# define LTHR and FTP to calculate custom Coggan heart rate and power zones
LTHR = # TODO: fill in a number for the lactate threshold heart rate [bpm]
FTP = # TODO: fill in a number for the functional threshold power [W]
hr_zones = calc_hr_zones ( LTHR )
power_zones = calc_power_zones ( FTP )
# calculate hr and power zones
df_zones = df . groupby ( 'date' ). apply ( agg_zones , hr_zones = hr_zones , power_zones = power_zones )
# ---------- power
df = df . set_index ( 'timestamp' )
# calculate power statistics
df_power = df . groupby ( 'date' ). apply ( agg_power , FTP = FTP )
# fill up dates for which we don't have an entry to get exponential weighted mean (ewm)
dates = df_power . index
df_power = df_power . reindex ( date_range )
# calculate ctl, atl and tsb
df_power [ 'chronic_training_load' ] = chronic_training_load ( df_power [ 'training_stress_score' ])
df_power [ 'acute_training_load' ] = acute_training_load ( df_power [ 'training_stress_score' ])
df_power [ 'training_stress_balance' ] = training_stress_balance ( df_power [ 'chronic_training_load' ], df_power [ 'acute_training_load' ])
# get back to indices for which there is a training session
df_power = df_power . loc [ dates ]如果您遇到问题，欢迎联系作者（[email protected]）。
该代码版权所有 © E. van Weenen, 2022，可根据软件随附的 MIT 许可证使用。
除了本许可证施加的法律限制之外，如果您将此软件用于学术出版物，则您有义务提供适当的归属。
E. van Weenen. cycling-stats: Calculate advanced cycling statistics from power and/or heart rate data, v0.1 (2022). github.com/evavanweenen/cycling-stats.
