mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-28 03:49:12 +08:00
Richard Frank
095f2dd65b
Issues appeared when we were close to the end of our historical data. Yielding DONE event with both perf and risk messages now
82 lines
3.0 KiB
Python
82 lines
3.0 KiB
Python
#
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# Copyright 2012 Quantopian, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from unittest import TestCase
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from datetime import timedelta
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import numpy as np
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from zipline.utils.test_utils import setup_logger
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import zipline.utils.factory as factory
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from zipline.test_algorithms import TestRegisterTransformAlgorithm
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from zipline.sources import SpecificEquityTrades, DataFrameSource
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from zipline.transforms import MovingAverage
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class TestTransformAlgorithm(TestCase):
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def setUp(self):
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setup_logger(self)
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self.trading_environment = factory.create_trading_environment()
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setup_logger(self)
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trade_history = factory.create_trade_history(
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133,
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[10.0, 10.0, 11.0, 11.0],
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[100, 100, 100, 300],
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timedelta(days=1),
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self.trading_environment
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)
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self.source = SpecificEquityTrades(event_list=trade_history)
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self.df_source, self.df = \
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factory.create_test_df_source(self.trading_environment)
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def test_source_as_input(self):
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algo = TestRegisterTransformAlgorithm(sids=[133])
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algo.run(self.source)
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self.assertEqual(len(algo.sources), 1)
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assert isinstance(algo.sources[0], SpecificEquityTrades)
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def test_multi_source_as_input_no_start_end(self):
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algo = TestRegisterTransformAlgorithm(sids=[133])
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with self.assertRaises(AssertionError):
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algo.run([self.source, self.df_source])
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def test_multi_source_as_input(self):
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algo = TestRegisterTransformAlgorithm(sids=[0, 1, 133])
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algo.run([self.source, self.df_source],
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start=self.df.index[0], end=self.df.index[-1])
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self.assertEqual(len(algo.sources), 2)
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def test_df_as_input(self):
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algo = TestRegisterTransformAlgorithm(sids=[0, 1])
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algo.run(self.df)
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assert isinstance(algo.sources[0], DataFrameSource)
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def test_run_twice(self):
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algo = TestRegisterTransformAlgorithm(sids=[0, 1])
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res1 = algo.run(self.df)
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res2 = algo.run(self.df)
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np.testing.assert_array_equal(res1, res2)
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def test_transform_registered(self):
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algo = TestRegisterTransformAlgorithm(sids=[133])
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algo.run(self.source)
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assert 'mavg' in algo.registered_transforms
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assert algo.registered_transforms['mavg']['args'] == (['price'],)
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assert algo.registered_transforms['mavg']['kwargs'] == \
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{'window_length': 2, 'market_aware': True}
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assert algo.registered_transforms['mavg']['class'] is MovingAverage
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