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71a34bf7ac
The daily/session bar reader's `spot_price` took the same parameters and returned the same kind of output as the minute bar reader's `get_value`. Standardize on one method to make a common interface, which may be formally factored out in a later patch; to help enable writing reader implementations or mixins which can be agnostic to the bar frequency.
120 lines
3.6 KiB
Python
120 lines
3.6 KiB
Python
#
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# Copyright 2016 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 itertools import permutations, product
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import numpy as np
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import pandas as pd
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from zipline.data.us_equity_pricing import PanelBarReader
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from zipline.testing import ExplodingObject
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from zipline.testing.fixtures import (
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WithAssetFinder,
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ZiplineTestCase,
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)
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from zipline.utils.calendars import get_calendar
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class WithPanelBarReader(WithAssetFinder):
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@classmethod
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def init_class_fixtures(cls):
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super(WithPanelBarReader, cls).init_class_fixtures()
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finder = cls.asset_finder
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trading_calendar = get_calendar('NYSE')
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items = finder.retrieve_all(finder.sids)
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major_axis = (
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trading_calendar.sessions_in_range if cls.FREQUENCY == 'daily'
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else trading_calendar.minutes_for_sessions_in_range
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)(cls.START_DATE, cls.END_DATE)
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minor_axis = ['open', 'high', 'low', 'close', 'volume']
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shape = tuple(map(len, [items, major_axis, minor_axis]))
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raw_data = np.arange(shape[0] * shape[1] * shape[2]).reshape(shape)
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cls.panel = pd.Panel(
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raw_data,
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items=items,
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major_axis=major_axis,
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minor_axis=minor_axis,
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)
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cls.reader = PanelBarReader(trading_calendar, cls.panel, cls.FREQUENCY)
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def test_get_value(self):
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panel = self.panel
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reader = self.reader
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for asset, date, field in product(*panel.axes):
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self.assertEqual(
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panel.loc[asset, date, field],
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reader.get_value(asset, date, field),
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)
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def test_duplicate_values(self):
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UNIMPORTANT_VALUE = 57
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panel = pd.Panel(
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UNIMPORTANT_VALUE,
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items=['a', 'b', 'b', 'a'],
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major_axis=['c'],
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minor_axis=['d'],
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)
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unused = ExplodingObject()
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axis_names = ['items', 'major_axis', 'minor_axis']
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for axis_order in permutations((0, 1, 2)):
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transposed = panel.transpose(*axis_order)
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with self.assertRaises(ValueError) as e:
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PanelBarReader(unused, transposed, 'daily')
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expected = (
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"Duplicate entries in Panel.{name}: ['a', 'b'].".format(
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name=axis_names[axis_order.index(0)],
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)
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)
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self.assertEqual(str(e.exception), expected)
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def test_sessions(self):
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sessions = self.reader.sessions
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self.assertEqual(self.NUM_SESSIONS, len(sessions))
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self.assertEqual(self.START_DATE, sessions[0])
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self.assertEqual(self.END_DATE, sessions[-1])
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class TestPanelDailyBarReader(WithPanelBarReader,
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ZiplineTestCase):
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FREQUENCY = 'daily'
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START_DATE = pd.Timestamp('2006-01-03', tz='utc')
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END_DATE = pd.Timestamp('2006-02-01', tz='utc')
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NUM_SESSIONS = 21
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class TestPanelMinuteBarReader(WithPanelBarReader,
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ZiplineTestCase):
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FREQUENCY = 'minute'
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START_DATE = pd.Timestamp('2015-12-23', tz='utc')
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END_DATE = pd.Timestamp('2015-12-24', tz='utc')
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NUM_SESSIONS = 2
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