mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-28 00:43:11 +08:00
81 lines
3.0 KiB
Python
81 lines
3.0 KiB
Python
#
|
|
# Copyright 2012 Quantopian, Inc.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
from unittest2 import TestCase
|
|
from datetime import timedelta
|
|
import numpy as np
|
|
|
|
from zipline.utils.test_utils import setup_logger
|
|
import zipline.utils.factory as factory
|
|
from zipline.test_algorithms import TestRegisterTransformAlgorithm
|
|
from zipline.sources import SpecificEquityTrades, DataFrameSource
|
|
from zipline.transforms import MovingAverage
|
|
|
|
|
|
class TestTransformAlgorithm(TestCase):
|
|
def setUp(self):
|
|
setup_logger(self)
|
|
self.trading_environment = factory.create_trading_environment()
|
|
setup_logger(self)
|
|
|
|
trade_history = factory.create_trade_history(
|
|
133,
|
|
[10.0, 10.0, 11.0, 11.0],
|
|
[100, 100, 100, 300],
|
|
timedelta(days=1),
|
|
self.trading_environment
|
|
)
|
|
self.source = SpecificEquityTrades(event_list=trade_history)
|
|
|
|
self.df_source, self.df = factory.create_test_df_source()
|
|
|
|
def test_source_as_input(self):
|
|
algo = TestRegisterTransformAlgorithm(sids=[133])
|
|
algo.run(self.source)
|
|
self.assertEqual(len(algo.sources), 1)
|
|
assert isinstance(algo.sources[0], SpecificEquityTrades)
|
|
|
|
def test_multi_source_as_input_no_start_end(self):
|
|
algo = TestRegisterTransformAlgorithm(sids=[133])
|
|
with self.assertRaises(AssertionError):
|
|
algo.run([self.source, self.df_source])
|
|
|
|
def test_multi_source_as_input(self):
|
|
algo = TestRegisterTransformAlgorithm(sids=[0, 1, 133])
|
|
algo.run([self.source, self.df_source],
|
|
start=self.df.index[0], end=self.df.index[-1])
|
|
self.assertEqual(len(algo.sources), 2)
|
|
|
|
def test_df_as_input(self):
|
|
algo = TestRegisterTransformAlgorithm(sids=[0, 1])
|
|
algo.run(self.df)
|
|
assert isinstance(algo.sources[0], DataFrameSource)
|
|
|
|
def test_run_twice(self):
|
|
algo = TestRegisterTransformAlgorithm(sids=[0, 1])
|
|
res1 = algo.run(self.df)
|
|
res2 = algo.run(self.df)
|
|
|
|
np.testing.assert_array_equal(res1, res2)
|
|
|
|
def test_transform_registered(self):
|
|
algo = TestRegisterTransformAlgorithm(sids=[133])
|
|
algo.run(self.source)
|
|
assert 'mavg' in algo.registered_transforms
|
|
assert algo.registered_transforms['mavg']['args'] == (['price'],)
|
|
assert algo.registered_transforms['mavg']['kwargs'] == \
|
|
{'days': 2, 'market_aware': True}
|
|
assert algo.registered_transforms['mavg']['class'] is MovingAverage
|