def test_error_band_cost_range_equiv(default_cost_err):
covering = datamodel.ErrorBandCost(
bands=[
datamodel.CostBand(
error_range=(-2, 2),
cost_function='constant',
cost_function_parameters=datamodel.ConstantCost(
cost=2.0, aggregation='sum', net=True
)
),
datamodel.CostBand(
error_range=(-np.inf, np.inf),
cost_function='constant',
cost_function_parameters=datamodel.ConstantCost(
cost=4.0, aggregation='sum', net=False
)
)
]
)
split = datamodel.ErrorBandCost(
bands=[
datamodel.CostBand(
error_range=(-2, 2),
cost_function='constant',
cost_function_parameters=datamodel.ConstantCost(
cost=2.0, aggregation='sum', net=True
)
),
datamodel.CostBand(
error_range=(-np.inf, -2),
cost_function='constant',
cost_function_parameters=datamodel.ConstantCost(
cost=4.0, aggregation='sum', net=False
)
),
datamodel.CostBand(
error_range=(2, np.inf),
cost_function='constant',
cost_function_parameters=datamodel.ConstantCost(
cost=4.0, aggregation='sum', net=False
)
)
]
)
fx = default_cost_err
obs = pd.Series(0, index=fx.index)
err_cov = deterministic.error_band_cost(
obs, fx, covering, deterministic.error)
err_split = deterministic.error_band_cost(
obs, fx, split, deterministic.error)
assert err_cov == err_split
def test_error_band_cost_no_bands(default_cost_err):
params = datamodel.ErrorBandCost(
bands=tuple()
)
fx = default_cost_err
obs = pd.Series(0, index=fx.index)
err = deterministic.error_band_cost(
obs, fx, params, deterministic.error)
assert err == 0
def test_error_band_cost(banded_cost_params):
ind = pd.date_range(start='2020-05-01T00:00Z', freq='1h', periods=8)
obs = pd.Series([1, 6, 1, 2, 2.00, 2.0, 0, 4], index=ind)
fx = pd.Series([1., 2, 3, 0, -0.1, 1.9, 3, 5], index=ind)
err = deterministic.error_band_cost(
obs, fx, banded_cost_params.parameters, deterministic.error)
exp = ((0 + 0 + 2 + -2 + 0.0 + -0.1 + 0 + 1) +
(0 + 0 + 0 + 0. + 0.0 + 0.00 + 3 * 0.9 + 0) +
(0 + -4 * -0.2 + 0 + 0. + -2.1 * -0.2 + 0.00 + 0 + 0))
assert err == exp
def test_error_band_cost_out_of_range(default_cost_err):
params = datamodel.ErrorBandCost(
bands=[datamodel.CostBand(
error_range=(10, 100),
cost_function='constant',
cost_function_parameters=datamodel.ConstantCost(
cost=2.0, aggregation='sum', net=True
)
)]
)
fx = default_cost_err
obs = pd.Series(0, index=fx.index)
err = deterministic.error_band_cost(
obs, fx, params, deterministic.error)
assert err == 0
def test_error_band_cost_out_of_times(default_cost_err):
params = datamodel.ErrorBandCost(
bands=[datamodel.CostBand(
error_range=(-10, 1),
cost_function='datetime',
cost_function_parameters=datamodel.DatetimeCost(
datetimes=[pd.Timestamp('2020-05-01T02:00-07:00')],
cost=[1.0],
aggregation='sum',
fill='forward',
net=True
)
)]
)
fx = default_cost_err
obs = pd.Series(0, index=fx.index)
err = deterministic.error_band_cost(
obs, fx, params, deterministic.error)
assert err == 0