def validate_daily_ac_power(observation, values):
"""
Run a number of validation checks on a daily timeseries of AC power.
Parameters
----------
observation : solarforecastarbiter.datamodel.Observation
Observation object that the data is associated with
values : pandas.Series
Series of observation values
Returns
-------
timestamp_flag, night_flag, limit_flag, stale_flag, interpolation_flag, clipping_flag : pandas.Series
Integer bitmask series from
:py:func:`.validator.check_timestamp_spacing`,
:py:func:`.validator.check_irradiance_day_night`,
:py:func:`.validator.check_power_limits`,
:py:func:`.validator.detect_stale_values`,
:py:func:`.validator.detect_interpolation`,
:py:func:`.validator.detect_clipping`
""" # NOQA: E501
timestamp_flag, night_flag, ac_limit_flag = validate_ac_power(observation,
values)
stale_flag, interpolation_flag = _validate_stale_interpolated(observation,
values)
clipping_flag = validator.detect_clipping(values, _return_mask=True)
return (timestamp_flag, night_flag, ac_limit_flag, stale_flag,
interpolation_flag, clipping_flag)
def validate_daily_ac_power(observation, values):
"""
Run a number of validation checks on a daily timeseries of AC power.
Parameters
----------
observation : solarforecastarbiter.datamodel.Observation
Observation object that the data is associated with
values : pandas.Series
Series of observation values
Returns
-------
tuple
Tuple of integer bitmask series of flags from the following tests, in
order,
`validator.check_timestamp_spacing`
`validator.detect_stale_values`
`validator.detect_interpolation`
`validator.detect_clipping`
"""
timestamp_flag = _validate_timestamp(observation, values)
stale_flag = validator.detect_stale_values(values, _return_mask=True)
interpolation_flag = validator.detect_interpolation(values,
_return_mask=True)
clipping_flag = validator.detect_clipping(values, _return_mask=True)
return (timestamp_flag, stale_flag, interpolation_flag, clipping_flag)
def test_detect_clipping(ghi_clipped):
placeholder = pd.Series(index=ghi_clipped.index, data=False)
expected = placeholder.copy()
# for window=4 and fraction_in_window=0.75
expected.iloc[3:6] = True
expected.iloc[14:17] = True
expected.iloc[18:20] = True
expected.iloc[25] = True
expected.iloc[30:36] = True
expected.iloc[38:46] = True
expected.iloc[56:60] = True
flags = validator.detect_clipping(ghi_clipped, window=4,
fraction_in_window=0.75, rtol=5e-3,
levels=4)
assert_series_equal(flags, expected)