mirror of
https://github.com/wassname/catalyst.git
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Thomas Wiecki
92 lines
3.4 KiB
Python
92 lines
3.4 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,
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DataFrameSource,
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DataPanelSource)
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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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self.panel_source, self.panel = \
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factory.create_test_panel_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_panel_as_input(self):
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algo = TestRegisterTransformAlgorithm(sids=[0, 1])
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algo.run(self.panel)
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assert isinstance(algo.sources[0], DataPanelSource)
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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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