Files
catalyst/tests/data/test_us_equity_pricing.py
T
Eddie Hebert 51eda06323 MAINT: Add equity to naming of bar data classes.
In preparation of adding futures, add equity to the names of both the
classes and methods for writing bcolz data. Futures data will use a
different minutes per day with a separate reader. This change will allow
both equity and futures fixtures to be side by side.

Also, break out the method which generates the dataframes and trading
days member into fixtures (`EquityMinuteBarData` and
`EquityDailyBarData`) on which the `*BarReader` fixture depends.  This
fixture is separated out to enable reader/writers in different formats
to use the same data setup. (There is internal code which needs to write
minute and daily bar data in a database format.)
2016-06-30 08:21:42 -04:00

357 lines
12 KiB
Python

#
# Copyright 2015 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 sys import maxsize
from nose_parameterized import parameterized
from numpy import (
arange,
datetime64,
)
from numpy.testing import (
assert_array_equal,
)
from pandas import (
DataFrame,
DatetimeIndex,
Timestamp,
)
from pandas.util.testing import assert_index_equal
from zipline.data.us_equity_pricing import (
BcolzDailyBarReader,
NoDataOnDate,
)
from zipline.pipeline.loaders.synthetic import (
OHLCV,
asset_start,
asset_end,
expected_bar_value,
expected_bar_values_2d,
make_bar_data,
)
from zipline.testing import seconds_to_timestamp
from zipline.testing.fixtures import (
WithBcolzEquityDailyBarReader,
ZiplineTestCase,
)
from zipline.utils.calendars import get_calendar
TEST_CALENDAR_START = Timestamp('2015-06-01', tz='UTC')
TEST_CALENDAR_STOP = Timestamp('2015-06-30', tz='UTC')
TEST_QUERY_START = Timestamp('2015-06-10', tz='UTC')
TEST_QUERY_STOP = Timestamp('2015-06-19', tz='UTC')
# One asset for each of the cases enumerated in load_raw_arrays_from_bcolz.
EQUITY_INFO = DataFrame(
[
# 1) The equity's trades start and end before query.
{'start_date': '2015-06-01', 'end_date': '2015-06-05'},
# 2) The equity's trades start and end after query.
{'start_date': '2015-06-22', 'end_date': '2015-06-30'},
# 3) The equity's data covers all dates in range.
{'start_date': '2015-06-02', 'end_date': '2015-06-30'},
# 4) The equity's trades start before the query start, but stop
# before the query end.
{'start_date': '2015-06-01', 'end_date': '2015-06-15'},
# 5) The equity's trades start and end during the query.
{'start_date': '2015-06-12', 'end_date': '2015-06-18'},
# 6) The equity's trades start during the query, but extend through
# the whole query.
{'start_date': '2015-06-15', 'end_date': '2015-06-25'},
],
index=arange(1, 7),
columns=['start_date', 'end_date'],
).astype(datetime64)
TEST_QUERY_ASSETS = EQUITY_INFO.index
class BcolzDailyBarTestCase(WithBcolzEquityDailyBarReader, ZiplineTestCase):
EQUITY_DAILY_BAR_START_DATE = TEST_CALENDAR_START
EQUITY_DAILY_BAR_END_DATE = TEST_CALENDAR_STOP
@classmethod
def make_equity_info(cls):
return EQUITY_INFO
@classmethod
def make_equity_daily_bar_data(cls):
return make_bar_data(
EQUITY_INFO,
cls.equity_daily_bar_days,
)
@classmethod
def init_class_fixtures(cls):
super(BcolzDailyBarTestCase, cls).init_class_fixtures()
cls.trading_days = get_calendar('NYSE').trading_days(
TEST_CALENDAR_START, TEST_CALENDAR_STOP
).index
@property
def assets(self):
return EQUITY_INFO.index
def trading_days_between(self, start, end):
return self.trading_days[self.trading_days.slice_indexer(start, end)]
def asset_start(self, asset_id):
return asset_start(EQUITY_INFO, asset_id)
def asset_end(self, asset_id):
return asset_end(EQUITY_INFO, asset_id)
def dates_for_asset(self, asset_id):
start, end = self.asset_start(asset_id), self.asset_end(asset_id)
return self.trading_days_between(start, end)
def test_write_ohlcv_content(self):
result = self.bcolz_daily_bar_ctable
for column in OHLCV:
idx = 0
data = result[column][:]
multiplier = 1 if column == 'volume' else 1000
for asset_id in self.assets:
for date in self.dates_for_asset(asset_id):
self.assertEqual(
expected_bar_value(
asset_id,
date,
column
) * multiplier,
data[idx],
)
idx += 1
self.assertEqual(idx, len(data))
def test_write_day_and_id(self):
result = self.bcolz_daily_bar_ctable
idx = 0
ids = result['id']
days = result['day']
for asset_id in self.assets:
for date in self.dates_for_asset(asset_id):
self.assertEqual(ids[idx], asset_id)
self.assertEqual(date, seconds_to_timestamp(days[idx]))
idx += 1
def test_write_attrs(self):
result = self.bcolz_daily_bar_ctable
expected_first_row = {
'1': 0,
'2': 5, # Asset 1 has 5 trading days.
'3': 12, # Asset 2 has 7 trading days.
'4': 33, # Asset 3 has 21 trading days.
'5': 44, # Asset 4 has 11 trading days.
'6': 49, # Asset 5 has 5 trading days.
}
expected_last_row = {
'1': 4,
'2': 11,
'3': 32,
'4': 43,
'5': 48,
'6': 57, # Asset 6 has 9 trading days.
}
expected_calendar_offset = {
'1': 0, # Starts on 6-01, 1st trading day of month.
'2': 15, # Starts on 6-22, 16th trading day of month.
'3': 1, # Starts on 6-02, 2nd trading day of month.
'4': 0, # Starts on 6-01, 1st trading day of month.
'5': 9, # Starts on 6-12, 10th trading day of month.
'6': 10, # Starts on 6-15, 11th trading day of month.
}
self.assertEqual(result.attrs['first_row'], expected_first_row)
self.assertEqual(result.attrs['last_row'], expected_last_row)
self.assertEqual(
result.attrs['calendar_offset'],
expected_calendar_offset,
)
assert_index_equal(
self.trading_days,
DatetimeIndex(result.attrs['calendar'], tz='UTC'),
)
def test_read_first_trading_day(self):
self.assertEqual(
self.bcolz_equity_daily_bar_reader.first_trading_day,
self.trading_days[0],
)
def _check_read_results(self, columns, assets, start_date, end_date):
results = self.bcolz_equity_daily_bar_reader.load_raw_arrays(
columns,
start_date,
end_date,
assets,
)
dates = self.trading_days_between(start_date, end_date)
for column, result in zip(columns, results):
assert_array_equal(
result,
expected_bar_values_2d(
dates,
EQUITY_INFO,
column,
)
)
@parameterized.expand([
(['open'],),
(['close', 'volume'],),
(['volume', 'high', 'low'],),
(['open', 'high', 'low', 'close', 'volume'],),
])
def test_read(self, columns):
self._check_read_results(
columns,
self.assets,
TEST_QUERY_START,
TEST_QUERY_STOP,
)
def test_start_on_asset_start(self):
"""
Test loading with queries that starts on the first day of each asset's
lifetime.
"""
columns = ['high', 'volume']
for asset in self.assets:
self._check_read_results(
columns,
self.assets,
start_date=self.asset_start(asset),
end_date=self.trading_days[-1],
)
def test_start_on_asset_end(self):
"""
Test loading with queries that start on the last day of each asset's
lifetime.
"""
columns = ['close', 'volume']
for asset in self.assets:
self._check_read_results(
columns,
self.assets,
start_date=self.asset_end(asset),
end_date=self.trading_days[-1],
)
def test_end_on_asset_start(self):
"""
Test loading with queries that end on the first day of each asset's
lifetime.
"""
columns = ['close', 'volume']
for asset in self.assets:
self._check_read_results(
columns,
self.assets,
start_date=self.trading_days[0],
end_date=self.asset_start(asset),
)
def test_end_on_asset_end(self):
"""
Test loading with queries that end on the last day of each asset's
lifetime.
"""
columns = ['close', 'volume']
for asset in self.assets:
self._check_read_results(
columns,
self.assets,
start_date=self.trading_days[0],
end_date=self.asset_end(asset),
)
def test_unadjusted_spot_price(self):
reader = self.bcolz_equity_daily_bar_reader
# At beginning
price = reader.spot_price(1, Timestamp('2015-06-01', tz='UTC'),
'close')
# Synthetic writes price for date.
self.assertEqual(108630.0, price)
# Middle
price = reader.spot_price(1, Timestamp('2015-06-02', tz='UTC'),
'close')
self.assertEqual(108631.0, price)
# End
price = reader.spot_price(1, Timestamp('2015-06-05', tz='UTC'),
'close')
self.assertEqual(108634.0, price)
# Another sid at beginning.
price = reader.spot_price(2, Timestamp('2015-06-22', tz='UTC'),
'close')
self.assertEqual(208651.0, price)
# Ensure that volume does not have float adjustment applied.
volume = reader.spot_price(1, Timestamp('2015-06-02', tz='UTC'),
'volume')
self.assertEqual(109631, volume)
def test_unadjusted_spot_price_no_data(self):
table = self.bcolz_daily_bar_ctable
reader = BcolzDailyBarReader(table)
# before
with self.assertRaises(NoDataOnDate):
reader.spot_price(2, Timestamp('2015-06-08', tz='UTC'), 'close')
# after
with self.assertRaises(NoDataOnDate):
reader.spot_price(4, Timestamp('2015-06-16', tz='UTC'), 'close')
def test_unadjusted_spot_price_empty_value(self):
reader = self.bcolz_equity_daily_bar_reader
# A sid, day and corresponding index into which to overwrite a zero.
zero_sid = 1
zero_day = Timestamp('2015-06-02', tz='UTC')
zero_ix = reader.sid_day_index(zero_sid, zero_day)
old = reader._spot_col('close')[zero_ix]
try:
# Write a zero into the synthetic pricing data at the day and sid,
# so that a read should now return -1.
# This a little hacky, in lieu of changing the synthetic data set.
reader._spot_col('close')[zero_ix] = 0
close = reader.spot_price(zero_sid, zero_day, 'close')
self.assertEqual(-1, close)
finally:
reader._spot_col('close')[zero_ix] = old
class BcolzDailyBarAlwaysReadAllTestCase(BcolzDailyBarTestCase):
"""
Force tests defined in BcolzDailyBarTestCase to always read the entire
column into memory before selecting desired asset data, when invoking
`load_raw_array`.
"""
BCOLZ_DAILY_BAR_READ_ALL_THRESHOLD = 0
class BcolzDailyBarNeverReadAllTestCase(BcolzDailyBarTestCase):
"""
Force tests defined in BcolzDailyBarTestCase to never read the entire
column into memory before selecting desired asset data, when invoking
`load_raw_array`.
"""
BCOLZ_DAILY_BAR_READ_ALL_THRESHOLD = maxsize