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TEST: Test forwarding of missing_value.
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@@ -18,6 +18,7 @@ from zipline.pipeline.data.testing import TestingDataSet
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from zipline.pipeline.term import AssetExists, NotSpecified
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from zipline.pipeline.expression import NUMEXPR_MATH_FUNCS
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from zipline.utils.numpy_utils import (
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bool_dtype,
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datetime64ns_dtype,
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float64_dtype,
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int64_dtype,
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@@ -335,10 +336,19 @@ class ObjectIdentityTestCase(TestCase):
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SomeFactor(dtype=1)
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def test_latest_on_different_dtypes(self):
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self.assertIsInstance(TestingDataSet.bool_col.latest, Filter)
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self.assertIsInstance(TestingDataSet.float_col.latest, Factor)
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self.assertIsInstance(TestingDataSet.datetime_col.latest, Factor)
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self.assertIsInstance(TestingDataSet.int_col.latest, Factor)
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factor_dtypes = (int64_dtype, float64_dtype, datetime64ns_dtype)
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for column in TestingDataSet.columns:
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if column.dtype == bool_dtype:
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self.assertIsInstance(column.latest, Filter)
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elif column.dtype in factor_dtypes:
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self.assertIsInstance(column.latest, Factor)
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else:
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self.fail(
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"Unknown dtype %s for column %s" % (column.dtype, column)
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)
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# These should be the same value, plus this has the convenient
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# property of correctly handling `NaN`.
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self.assertIs(column.missing_value, column.latest.missing_value)
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def test_failure_timing_on_bad_missing_values(self):
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