Files
catalyst/tests/test_benchmark.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

204 lines
7.1 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.
import numpy as np
import pandas as pd
from zipline.data.data_portal import DataPortal
from zipline.errors import (
BenchmarkAssetNotAvailableTooEarly,
BenchmarkAssetNotAvailableTooLate,
InvalidBenchmarkAsset)
from zipline.sources.benchmark_source import BenchmarkSource
from zipline.testing import (
MockDailyBarReader,
create_minute_bar_data,
tmp_bcolz_equity_minute_bar_reader,
)
from zipline.testing.fixtures import (
WithDataPortal,
WithSimParams,
WithTradingSchedule,
ZiplineTestCase,
)
class TestBenchmark(WithDataPortal, WithSimParams, WithTradingSchedule,
ZiplineTestCase):
START_DATE = pd.Timestamp('2006-01-03', tz='utc')
END_DATE = pd.Timestamp('2006-12-29', tz='utc')
@classmethod
def make_equity_info(cls):
return pd.DataFrame.from_dict(
{
1: {
"start_date": cls.START_DATE,
"end_date": cls.END_DATE + pd.Timedelta(days=1)
},
2: {
"start_date": cls.START_DATE,
"end_date": cls.END_DATE + pd.Timedelta(days=1)
},
3: {
"start_date": pd.Timestamp('2006-05-26', tz='utc'),
"end_date": pd.Timestamp('2006-08-09', tz='utc')
},
4: {
"start_date": cls.START_DATE,
"end_date": cls.END_DATE + pd.Timedelta(days=1)
},
},
orient='index',
)
@classmethod
def make_adjustment_writer_equity_daily_bar_reader(cls):
return MockDailyBarReader()
@classmethod
def make_stock_dividends_data(cls):
declared_date = cls.sim_params.trading_days[45]
ex_date = cls.sim_params.trading_days[50]
record_date = pay_date = cls.sim_params.trading_days[55]
return pd.DataFrame({
'sid': np.array([4], dtype=np.uint32),
'payment_sid': np.array([5], dtype=np.uint32),
'ratio': np.array([2], dtype=np.float64),
'declared_date': np.array([declared_date], dtype='datetime64[ns]'),
'ex_date': np.array([ex_date], dtype='datetime64[ns]'),
'record_date': np.array([record_date], dtype='datetime64[ns]'),
'pay_date': np.array([pay_date], dtype='datetime64[ns]'),
})
def test_normal(self):
days_to_use = self.sim_params.trading_days[1:]
source = BenchmarkSource(
1, self.env, self.trading_schedule, days_to_use, self.data_portal
)
# should be the equivalent of getting the price history, then doing
# a pct_change on it
manually_calculated = self.data_portal.get_history_window(
[1], days_to_use[-1], len(days_to_use), "1d", "close"
)[1].pct_change()
# compare all the fields except the first one, for which we don't have
# data in manually_calculated
for idx, day in enumerate(days_to_use[1:]):
self.assertEqual(
source.get_value(day),
manually_calculated[idx + 1]
)
def test_asset_not_trading(self):
benchmark = self.env.asset_finder.retrieve_asset(3)
benchmark_start = benchmark.start_date
benchmark_end = benchmark.end_date
with self.assertRaises(BenchmarkAssetNotAvailableTooEarly) as exc:
BenchmarkSource(
3,
self.env,
self.trading_schedule,
self.sim_params.trading_days[1:],
self.data_portal
)
self.assertEqual(
'3 does not exist on %s. It started trading on %s.' %
(self.sim_params.trading_days[1], benchmark_start),
exc.exception.message
)
with self.assertRaises(BenchmarkAssetNotAvailableTooLate) as exc2:
BenchmarkSource(
3,
self.env,
self.trading_schedule,
self.sim_params.trading_days[120:],
self.data_portal
)
self.assertEqual(
'3 does not exist on %s. It stopped trading on %s.' %
(self.sim_params.trading_days[-1], benchmark_end),
exc2.exception.message
)
def test_asset_IPOed_same_day(self):
# gotta get some minute data up in here.
# add sid 4 for a couple of days
minutes = self.trading_schedule.execution_minutes_for_days_in_range(
self.sim_params.trading_days[0],
self.sim_params.trading_days[5]
)
tmp_reader = tmp_bcolz_equity_minute_bar_reader(
self.trading_schedule,
self.trading_schedule.all_execution_days,
create_minute_bar_data(minutes, [2]),
)
with tmp_reader as reader:
data_portal = DataPortal(
self.env.asset_finder, self.trading_schedule,
first_trading_day=reader.first_trading_day,
equity_minute_reader=reader,
equity_daily_reader=self.bcolz_equity_daily_bar_reader,
adjustment_reader=self.adjustment_reader,
)
source = BenchmarkSource(
2,
self.env,
self.trading_schedule,
self.sim_params.trading_days,
data_portal
)
days_to_use = self.sim_params.trading_days
# first value should be 0.0, coming from daily data
self.assertAlmostEquals(0.0, source.get_value(days_to_use[0]))
manually_calculated = data_portal.get_history_window(
[2], days_to_use[-1],
len(days_to_use),
"1d",
"close",
)[2].pct_change()
for idx, day in enumerate(days_to_use[1:]):
self.assertEqual(
source.get_value(day),
manually_calculated[idx + 1]
)
def test_no_stock_dividends_allowed(self):
# try to use sid(4) as benchmark, should blow up due to the presence
# of a stock dividend
with self.assertRaises(InvalidBenchmarkAsset) as exc:
BenchmarkSource(
4, self.env, self.trading_schedule,
self.sim_params.trading_days, self.data_portal
)
self.assertEqual("4 cannot be used as the benchmark because it has a "
"stock dividend on 2006-03-16 00:00:00. Choose "
"another asset to use as the benchmark.",
exc.exception.message)