This python package contains tools to handle sport gps tracks (tcx, gpx, ...)
Project description
# analytracks
Workout tracks analytics
## Installation
pip install -e .
## Parsing
```python
run1 = atrk.tracks.Track('LLN_10miles.tcx') # should also work with gpx
run1.points # track points
run1.data # track data
run1.rideRun # should be either 'ride' or 'run'
```
## Pre-processing
```python
run1.add_google_elevation() # assuming you have an api key
# otherwise use ele_name='ele'
# it will use elevations from the track file
run1.add_slope(sf=0.05,ele_name='googleElevation',plot=True) # or ele_name='ele'
run1.add_speed(sf=0.05,plot=True)
```
## Heart Rate parameters fitting
### initial parameters
```python
x0 = {'delay': 0, # delay between hr and power output [s]
'hr_max': 185,
'hr_rest': 135.46978177728184,
'hr_slope': 2.9580335634755954, # bpm/watt if power expressed in Watt
'k_e': 1e-05, # sensitivity to fatigue
'k_f': 0.04, # 1/t_f : falling time constant
'k_r': 0.04, # 1/t_r : raising time constant
'slope_sf': 0.1, # slope smoothing factor
'speed_sf': 0.1} # speed smoothing factor
```
### parameters fitting
```python
run1.hr_fit(x0=x0,to_tune=['hr_rest','hr_slope','k_f','k_r'])
run1.hr_sim(ele_name='googleElevation') # simulation
run1.hr_plot() # plot of the results
```
Workout tracks analytics
## Installation
pip install -e .
## Parsing
```python
run1 = atrk.tracks.Track('LLN_10miles.tcx') # should also work with gpx
run1.points # track points
run1.data # track data
run1.rideRun # should be either 'ride' or 'run'
```
## Pre-processing
```python
run1.add_google_elevation() # assuming you have an api key
# otherwise use ele_name='ele'
# it will use elevations from the track file
run1.add_slope(sf=0.05,ele_name='googleElevation',plot=True) # or ele_name='ele'
run1.add_speed(sf=0.05,plot=True)
```
## Heart Rate parameters fitting
### initial parameters
```python
x0 = {'delay': 0, # delay between hr and power output [s]
'hr_max': 185,
'hr_rest': 135.46978177728184,
'hr_slope': 2.9580335634755954, # bpm/watt if power expressed in Watt
'k_e': 1e-05, # sensitivity to fatigue
'k_f': 0.04, # 1/t_f : falling time constant
'k_r': 0.04, # 1/t_r : raising time constant
'slope_sf': 0.1, # slope smoothing factor
'speed_sf': 0.1} # speed smoothing factor
```
### parameters fitting
```python
run1.hr_fit(x0=x0,to_tune=['hr_rest','hr_slope','k_f','k_r'])
run1.hr_sim(ele_name='googleElevation') # simulation
run1.hr_plot() # plot of the results
```
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