docstr: Test that slices can be created by indexing into a term, and that they
  have the correct shape when used as inputs.
docstr_tok: ["Test","that","slices","can","be","created","by","indexing","into","a","term",",","and","that","they","have","the","correct","shape","when","used","as","inputs","."]
code: def _test_slice(self, my_asset_column, window_length_):
      """
      Test that slices can be created by indexing into a term, and that they
      have the correct shape when used as inputs.
      """
      sids = self.sids
      my_asset = self.asset_finder.retrieve_asset(
          self.sids[my_asset_column]
      )
  
      returns = Returns(window_length=2, inputs=[self.col])
      returns_slice = returns[my_asset]
  
      class UsesSlicedInput(CustomFactor):
          window_length = window_length_
          inputs = [returns, returns_slice]
  
          def compute(self, today, assets, out, returns, returns_slice):
              # Make sure that our slice is the correct shape (i.e. has only
              # one column) and that it has the same values as the original
              # returns factor from which it is derived.
              assert returns_slice.shape == (self.window_length, 1)
              assert returns.shape == (self.window_length, len(sids))
              check_arrays(
                  returns_slice[:, 0], returns[:, my_asset_column]
              )
  
      # Assertions about the expected slice data are made in the `compute`
      # function of our custom factor above.
      self.run_pipeline(
          Pipeline(columns={"uses_sliced_input": UsesSlicedInput()}),
          self.pipeline_start_date,
          self.pipeline_end_date,
      )
  
imports: from numpy import where
  from pandas import Int64Index, Timestamp
  from pandas.util.testing import assert_frame_equal
  from catalyst.assets import Asset
  from catalyst.errors import NonExistentAssetInTimeFrame, NonSliceableTerm, NonWindowSafeInput, UnsupportedPipelineOutput
  from catalyst.pipeline import CustomFactor, Pipeline
  from catalyst.pipeline.data import USEquityPricing
  from catalyst.pipeline.data.testing import TestingDataSet
  from catalyst.pipeline.factors.equity import Returns, RollingLinearRegressionOfReturns, RollingPearsonOfReturns, RollingSpearmanOfReturns, SimpleMovingAverage
  from catalyst.testing import AssetID, AssetIDPlusDay, check_arrays, OpenPrice, parameter_space
  from catalyst.testing.fixtures import WithSeededRandomPipelineEngine, CatalystTestCase
  from catalyst.utils.numpy_utils import datetime64ns_dtype
label_desc: Use image node_id 2 for calling the SliceTestCase obj's underlying member method code with example usage: obj._test_slice(my_asset_column, window_length_) without return types