In [7]:

import pandas as pd

from lactopy.lactate_models.general.OBLA import OBLA

import pandas as pd from lactopy.lactate_models.general.OBLA import OBLA

In [8]:

df = pd.read_csv('../tests/test_data/lactate_test_data copy.csv')

df = pd.read_csv('../tests/test_data/lactate_test_data copy.csv')

In [ ]:

# fit model returns a scikit learn like model object
obla = OBLA()
obla.fit(df['watt'], df['lactate'])

# fit model returns a scikit learn like model object obla = OBLA() obla.fit(df['watt'], df['lactate'])

Out[ ]:

OBLA()

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In [ ]:

# plot fit of data
obla.plot.plot_fit()

# plot fit of data obla.plot.plot_fit()

Out[ ]:

<Axes: title={'center': 'Lactate Model Fit'}, xlabel='Intensity', ylabel='Lactate'>

In [ ]:

# predict intensity at 4 mmol
obla.predict(4)

# predict intensity at 4 mmol obla.predict(4)

Out[ ]:

np.float64(145.93695290778828)

In [ ]:

# Plot the prediction at 4 mmol
obla.plot.plot_predictions(4)

# Plot the prediction at 4 mmol obla.plot.plot_predictions(4)

Out[ ]:

<Axes: title={'center': 'Lactate Model Fit'}, xlabel='Intensity', ylabel='Lactate'>

plot of all different models¶