def wdf_big():
athlete = models.Athlete(cp=200, w_prime=20000, weight=80)
wdf = models.WorkoutDataFrame(
pd.read_csv('tests/example_files/workout_1.csv'))
wdf = wdf.set_index('time')
wdf.athlete = athlete
return wdf
def wdf():
data = {'time': range(10), 'heartrate': range(10), 'power': range(10)}
athlete = models.Athlete(name='Chris', weight=80, ftp=300)
wdf = models.WorkoutDataFrame(data)
wdf = wdf.set_index('time')
wdf.athlete = athlete
return wdf
def test_is_valid_invalid_sample_rate(self):
data = {
'time': range(0, 20, 2),
'heartrate': range(10),
'power': range(10)
}
wdf = models.WorkoutDataFrame(data)
wdf = wdf.set_index('time')
with pytest.raises(
exceptions.WorkoutDataFrameValidationException) as e:
wdf.is_valid()
assert e.message == '[.\n]*Sample rate is not \(consistent\) 1Hz[.\n]*'
def test_is_valid_invalid_max_value(self):
data = {
'time': range(10),
'heartrate': range(10),
'power': range(10000, 10010)
}
wdf = models.WorkoutDataFrame(data)
wdf = wdf.set_index('time')
with pytest.raises(
exceptions.WorkoutDataFrameValidationException) as e:
wdf.is_valid()
assert e.message == '[.\n]*Column \'power\' has values > 3000[.\n]*'
def test_is_valid_invalid_dtype(self):
data = {
'time': range(10),
'heartrate': np.arange(0, 15, 1.5),
'power': range(10)
}
wdf = models.WorkoutDataFrame(data)
wdf = wdf.set_index('time')
with pytest.raises(
exceptions.WorkoutDataFrameValidationException) as e:
wdf.is_valid()
assert e.message == '[.\n]*Column \'heartrate\' is not of dtype[.\n]*'
def test_empty_init(self):
wdf = models.WorkoutDataFrame()
assert isinstance(wdf, pd.DataFrame)
assert isinstance(wdf, models.WorkoutDataFrame)
