mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-28 07:32:47 +08:00
Scott Sanderson
26fd6fda8b
- Fixes an error where Modeling API data known as of the close of `day N` would be shown to algorithms during `before_trading_start` as of the close of the same day. Algorithms should now only receive data during `before_trading_start/handle_data` that was known as of the simulation time at which the function would be called. - All Term instances now have a `mask` attribute that must be a `Filter` or an instance of `AssetExists()`. `mask` can be used to specify that a Factor should be computed in a manner that ignores the values that were not `True` in the mask. - Changed the interface for `FFCLoader.load_adjusted_array` and `Term._compute` from `(columns, mask)`, with mask as a DataFrame, to `(columns, dates, assets, mask)`, where mask is a numpy array. This is primarily to avoid having to reconstruct extra DataFrames when using masks produced by non `AssetExists` filters. - Adds `BoundColumn.latest`, which gives the most-recently-known value of a column.
294 lines
8.2 KiB
Python
294 lines
8.2 KiB
Python
"""
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Tests for Term.
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"""
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from itertools import product
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from unittest import TestCase
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from numpy import (
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float32,
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uint32,
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uint8,
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)
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from zipline.data.dataset import (
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Column,
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DataSet,
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)
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from zipline.errors import (
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InputTermNotAtomic,
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TermInputsNotSpecified,
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WindowLengthNotSpecified,
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)
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from zipline.modelling.expression import NUMEXPR_MATH_FUNCS
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from zipline.modelling.factor import Factor
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from zipline.modelling.graph import TermGraph
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from zipline.modelling.term import AssetExists, NotSpecified
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class SomeDataSet(DataSet):
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foo = Column(float32)
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bar = Column(uint32)
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buzz = Column(uint8)
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class SomeFactor(Factor):
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window_length = 5
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inputs = [SomeDataSet.foo, SomeDataSet.bar]
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class NoLookbackFactor(Factor):
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window_length = 0
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class SomeOtherFactor(Factor):
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window_length = 5
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inputs = [SomeDataSet.bar, SomeDataSet.buzz]
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SomeFactorAlias = SomeFactor
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def gen_equivalent_factors():
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"""
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Return an iterator of SomeFactor instances that should all be the same
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object.
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"""
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yield SomeFactor()
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yield SomeFactor(inputs=NotSpecified)
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yield SomeFactor(SomeFactor.inputs)
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yield SomeFactor(inputs=SomeFactor.inputs)
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yield SomeFactor([SomeDataSet.foo, SomeDataSet.bar])
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yield SomeFactor(window_length=SomeFactor.window_length)
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yield SomeFactor(window_length=NotSpecified)
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yield SomeFactor(
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[SomeDataSet.foo, SomeDataSet.bar],
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window_length=NotSpecified,
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)
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yield SomeFactor(
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[SomeDataSet.foo, SomeDataSet.bar],
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window_length=SomeFactor.window_length,
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)
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yield SomeFactorAlias()
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def to_dict(l):
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"""
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Convert a list to a dict with keys drawn from '0', '1', '2', ...
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Example
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-------
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>>> to_dict([2, 3, 4])
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{'0': 2, '1': 3, '2': 4}
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"""
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return dict(zip(map(str, range(len(l))), l))
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class DependencyResolutionTestCase(TestCase):
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def setup(self):
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pass
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def teardown(self):
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pass
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def test_single_factor(self):
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"""
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Test dependency resolution for a single factor.
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"""
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def check_output(graph):
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resolution_order = list(graph.ordered())
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self.assertEqual(len(resolution_order), 4)
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self.assertIs(resolution_order[0], AssetExists())
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self.assertEqual(
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set([resolution_order[1], resolution_order[2]]),
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set([SomeDataSet.foo, SomeDataSet.bar]),
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)
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self.assertEqual(resolution_order[-1], SomeFactor())
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self.assertEqual(graph.node[SomeDataSet.foo]['extra_rows'], 4)
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self.assertEqual(graph.node[SomeDataSet.bar]['extra_rows'], 4)
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for foobar in gen_equivalent_factors():
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check_output(TermGraph(to_dict([foobar])))
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def test_single_factor_instance_args(self):
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"""
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Test dependency resolution for a single factor with arguments passed to
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the constructor.
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"""
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bar, buzz = SomeDataSet.bar, SomeDataSet.buzz
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graph = TermGraph(to_dict([SomeFactor([bar, buzz], window_length=5)]))
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resolution_order = list(graph.ordered())
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# SomeFactor, its inputs, and AssetExists()
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self.assertEqual(len(resolution_order), 4)
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self.assertIs(resolution_order[0], AssetExists())
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self.assertEqual(graph.extra_rows[AssetExists()], 4)
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self.assertEqual(
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set([resolution_order[1], resolution_order[2]]),
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set([bar, buzz]),
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)
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self.assertEqual(
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resolution_order[-1],
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SomeFactor([bar, buzz], window_length=5),
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)
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self.assertEqual(graph.extra_rows[bar], 4)
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self.assertEqual(graph.extra_rows[buzz], 4)
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def test_reuse_atomic_terms(self):
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"""
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Test that raw inputs only show up in the dependency graph once.
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"""
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f1 = SomeFactor([SomeDataSet.foo, SomeDataSet.bar])
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f2 = SomeOtherFactor([SomeDataSet.bar, SomeDataSet.buzz])
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graph = TermGraph(to_dict([f1, f2]))
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resolution_order = list(graph.ordered())
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# bar should only appear once.
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self.assertEqual(len(resolution_order), 6)
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indices = {
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term: resolution_order.index(term)
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for term in resolution_order
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}
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self.assertEqual(indices[AssetExists()], 0)
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# Verify that f1's dependencies will be computed before f1.
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self.assertLess(indices[SomeDataSet.foo], indices[f1])
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self.assertLess(indices[SomeDataSet.bar], indices[f1])
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# Verify that f2's dependencies will be computed before f2.
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self.assertLess(indices[SomeDataSet.bar], indices[f2])
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self.assertLess(indices[SomeDataSet.buzz], indices[f2])
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def test_disallow_recursive_lookback(self):
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with self.assertRaises(InputTermNotAtomic):
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SomeFactor(inputs=[SomeFactor(), SomeDataSet.foo])
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class ObjectIdentityTestCase(TestCase):
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def assertSameObject(self, *objs):
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first = objs[0]
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for obj in objs:
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self.assertIs(first, obj)
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def test_instance_caching(self):
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self.assertSameObject(*gen_equivalent_factors())
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self.assertIs(
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SomeFactor(window_length=SomeFactor.window_length + 1),
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SomeFactor(window_length=SomeFactor.window_length + 1),
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)
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self.assertIs(
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SomeFactor(dtype=int),
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SomeFactor(dtype=int),
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)
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self.assertIs(
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SomeFactor(inputs=[SomeFactor.inputs[1], SomeFactor.inputs[0]]),
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SomeFactor(inputs=[SomeFactor.inputs[1], SomeFactor.inputs[0]]),
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)
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def test_instance_non_caching(self):
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f = SomeFactor()
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# Different window_length.
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self.assertIsNot(
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f,
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SomeFactor(window_length=SomeFactor.window_length + 1),
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)
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# Different dtype
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self.assertIsNot(
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f,
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SomeFactor(dtype=int)
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)
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# Reordering inputs changes semantics.
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self.assertIsNot(
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f,
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SomeFactor(inputs=[SomeFactor.inputs[1], SomeFactor.inputs[0]]),
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)
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def test_instance_non_caching_redefine_class(self):
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orig_foobar_instance = SomeFactorAlias()
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class SomeFactor(Factor):
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window_length = 5
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inputs = [SomeDataSet.foo, SomeDataSet.bar]
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self.assertIsNot(orig_foobar_instance, SomeFactor())
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def test_instance_caching_binops(self):
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f = SomeFactor()
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g = SomeOtherFactor()
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for lhs, rhs in product([f, g], [f, g]):
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self.assertIs((lhs + rhs), (lhs + rhs))
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self.assertIs((lhs - rhs), (lhs - rhs))
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self.assertIs((lhs * rhs), (lhs * rhs))
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self.assertIs((lhs / rhs), (lhs / rhs))
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self.assertIs((lhs ** rhs), (lhs ** rhs))
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self.assertIs((1 + rhs), (1 + rhs))
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self.assertIs((rhs + 1), (rhs + 1))
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self.assertIs((1 - rhs), (1 - rhs))
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self.assertIs((rhs - 1), (rhs - 1))
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self.assertIs((2 * rhs), (2 * rhs))
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self.assertIs((rhs * 2), (rhs * 2))
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self.assertIs((2 / rhs), (2 / rhs))
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self.assertIs((rhs / 2), (rhs / 2))
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self.assertIs((2 ** rhs), (2 ** rhs))
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self.assertIs((rhs ** 2), (rhs ** 2))
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self.assertIs((f + g) + (f + g), (f + g) + (f + g))
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def test_instance_caching_unary_ops(self):
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f = SomeFactor()
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self.assertIs(-f, -f)
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self.assertIs(--f, --f)
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self.assertIs(---f, ---f)
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def test_instance_caching_math_funcs(self):
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f = SomeFactor()
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for funcname in NUMEXPR_MATH_FUNCS:
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method = getattr(f, funcname)
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self.assertIs(method(), method())
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def test_bad_input(self):
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class SomeFactor(Factor):
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pass
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class SomeFactorDefaultInputs(Factor):
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inputs = (SomeDataSet.foo, SomeDataSet.bar)
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class SomeFactorDefaultLength(Factor):
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window_length = 10
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with self.assertRaises(TermInputsNotSpecified):
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SomeFactor(window_length=1)
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with self.assertRaises(TermInputsNotSpecified):
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SomeFactorDefaultLength()
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with self.assertRaises(WindowLengthNotSpecified):
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SomeFactor(inputs=(SomeDataSet.foo,))
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with self.assertRaises(WindowLengthNotSpecified):
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SomeFactorDefaultInputs()
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