def test_downsample_non_windowed_factor(self):
sma = SimpleMovingAverage(
inputs=[TestingDataSet.float_col],
window_length=5,
)
self.check_downsampled_term(((sma + sma) / 2).rank())
def test_downsample_nonwindowed_classifier(self):
sma = SimpleMovingAverage(
inputs=[TestingDataSet.float_col],
window_length=5,
)
self.check_downsampled_term(sma.quantiles(5))
def test_downsample_nonwindowed_filter(self):
sma = SimpleMovingAverage(
inputs=[TestingDataSet.float_col],
window_length=5,
)
self.check_downsampled_term(sma > 5)
def test_downsample_windowed_filter(self):
sma = SimpleMovingAverage(
inputs=[TestingDataSet.float_col],
window_length=5,
)
self.check_downsampled_term(All(inputs=[sma.top(4)], window_length=5))
def test_downsample_windowed_factor(self):
self.check_downsampled_term(
SimpleMovingAverage(
inputs=[TestingDataSet.float_col],
window_length=5,
))
def test_window_safety_of_slices(self):
"""
Test that slices correctly inherit the `window_safe` property of the
term from which they are derived.
"""
col = self.col
my_asset = self.asset_finder.retrieve_asset(self.sids[0])
# SimpleMovingAverage is not window safe.
sma = SimpleMovingAverage(inputs=[self.col], window_length=10)
sma_slice = sma[my_asset]
class UsesSlicedInput(CustomFactor):
window_length = 1
inputs = [sma_slice]
def compute(self, today, assets, out, sma_slice):
pass
with self.assertRaises(NonWindowSafeInput):
self.run_pipeline(
Pipeline(columns={'uses_sliced_input': UsesSlicedInput()}),
self.pipeline_start_date,
self.pipeline_end_date,
)
# Make sure that slices of custom factors are not window safe.
class MyUnsafeFactor(CustomFactor):
window_length = 1
inputs = [col]
def compute(self, today, assets, out, col):
pass
my_unsafe_factor = MyUnsafeFactor()
my_unsafe_factor_slice = my_unsafe_factor[my_asset]
class UsesSlicedInput(CustomFactor):
window_length = 1
inputs = [my_unsafe_factor_slice]
def compute(self, today, assets, out, my_unsafe_factor_slice):
pass
with self.assertRaises(NonWindowSafeInput):
self.run_pipeline(
Pipeline(columns={'uses_sliced_input': UsesSlicedInput()}),
self.pipeline_start_date,
self.pipeline_end_date,
)
# Create a window safe factor.
class MySafeFactor(CustomFactor):
window_length = 1
inputs = [col]
window_safe = True
def compute(self, today, assets, out, col):
pass
my_safe_factor = MySafeFactor()
my_safe_factor_slice = my_safe_factor[my_asset]
# Make sure that correlations are not safe if either the factor *or*
# the target slice are not window safe.
with self.assertRaises(NonWindowSafeInput):
my_unsafe_factor.pearsonr(
target=my_safe_factor_slice,
correlation_length=10,
)
with self.assertRaises(NonWindowSafeInput):
my_safe_factor.pearsonr(
target=my_unsafe_factor_slice,
correlation_length=10,
)
def test_downsample_nonwindowed_classifier(self):
sma = SimpleMovingAverage(
inputs=[TestingDataSet.float_col],
window_length=5,
)
self.check_downsampled_term(sma.quantiles(5))
def test_downsample_windowed_filter(self):
sma = SimpleMovingAverage(
inputs=[TestingDataSet.float_col],
window_length=5,
)
self.check_downsampled_term(All(inputs=[sma.top(4)], window_length=5))