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Better unittest coverage. DataFrameSource is now filtering sids. Fixed outstanding issues.

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This commit is contained in:
Thomas Wiecki
2012-09-21 11:59:46 -04:00
parent 2dbf905d43
commit 4324f95f36
10 changed files with 143 additions and 159 deletions
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tests/test_transforms.py
+8 -49
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@@ -10,13 +10,14 @@ from zipline.utils.test_utils import setup_logger
from zipline.utils.date_utils import utcnow
from zipline.gens.tradegens import SpecificEquityTrades
from zipline.gens.transform import StatefulTransform, EventWindow, BatchTransform, batch_transform
from zipline.gens.transform import StatefulTransform, EventWindow
from zipline.gens.vwap import VWAP
from zipline.gens.mavg import MovingAverage
from zipline.gens.stddev import MovingStandardDev
from zipline.gens.returns import Returns
import zipline.utils.factory as factory
from zipline import TradingAlgorithm
from zipline.test_algorithms import BatchTransformAlgorithm
def to_dt(msg):
return ndict({'dt': msg})
@@ -288,36 +289,7 @@ class FinanceTransformsTestCase(TestCase):
############################################################
# Test BatchTransform
class NoopBatchTransform(BatchTransform):
def get_value(self, data):
return data.price
@batch_transform
def noop_batch_decorator(data):
return data.price
class BatchTransformAlgorithm(TradingAlgorithm):
def initialize(self, *args, **kwargs):
self.history_class = []
self.history_decorator = []
self.days = 3
self.noop_class = NoopBatchTransform(sids=[0, 1],
market_aware=False,
refresh_period=2,
delta=timedelta(days=self.days))
self.noop_decorator = noop_batch_decorator(sids=[0, 1],
market_aware=False,
refresh_period=2,
delta=timedelta(days=self.days))
def handle_data(self, data):
window_class = self.noop_class.handle_data(data)
window_decorator = self.noop_decorator.handle_data(data)
self.history_class.append(window_class)
self.history_decorator.append(window_decorator)
class BatchTransformTestCase():
class BatchTransformTestCase(TestCase):
def setUp(self):
setup_logger(self)
self.source, self.df = factory.create_test_df_source()
@@ -329,21 +301,8 @@ class BatchTransformTestCase():
assert algo.history_class[:2] == algo.history_decorator[:2] == [None, None], "First two iterations should return None"
# test overloaded class
# every 2nd event should be identical because of refresh_period=2
# not sure why actual length gets up to 4, bug in EventWindow?
assert np.all(algo.history_class[2][0].values == [2, 4, 6])
assert np.all(algo.history_class[2][1].values == [3, 5, 7])
assert np.all(algo.history_class[3][0].values == [2, 4, 6])
assert np.all(algo.history_class[3][1].values == [3, 5, 7])
assert np.all(algo.history_class[4][0].values == [4, 6, 8, 10])
assert np.all(algo.history_class[4][1].values == [5, 7, 9, 11])
# test decorator
assert np.all(algo.history_decorator[2][0].values == [2, 4, 6])
assert np.all(algo.history_decorator[2][1].values == [3, 5, 7])
assert np.all(algo.history_decorator[3][0].values == [2, 4, 6])
assert np.all(algo.history_decorator[3][1].values == [3, 5, 7])
assert np.all(algo.history_decorator[4][0].values == [4, 6, 8, 10])
assert np.all(algo.history_decorator[4][1].values == [5, 7, 9, 11])
for test_history in [algo.history_class, algo.history_decorator]:
self.assertTrue(np.all(test_history[2].values.flatten() == range(4, 10)))
self.assertTrue(np.all(test_history[3].values.flatten() == range(4, 10)))
self.assertTrue(np.all(test_history[4].values.flatten() == range(6, 14)))