mirror of
https://github.com/wassname/catalyst.git
synced 2026-07-01 12:18:17 +08:00
Scott Sanderson
3395b33f1e
- Return a value from `verify_all_indices_unique` so that `panel` isn't unconditionally `None` in `PanelDailyBarReader`. - Fix a bug where we always set the volume of every asset to `1e9`. - Add minimal suite of tests for get_spot_value, which catch both of the above. NOTE: There are still several issues with `PanelDailyBarReader`. The docstring for `get_spot_value` claims that it will return -1 on days where an asset didn't trade, which isn't the case. It also claims that it will raise `NoDataOnDate` when a request is made outside the panel range, but it just raises a KeyError. We also still have no coverage for `load_raw_arrays`, so it's likely that there are more bugs lurking.
94 lines
2.8 KiB
Python
94 lines
2.8 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 PanelDailyBarReader
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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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WithNYSETradingDays,
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ZiplineTestCase,
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)
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class TestPanelDailyBarReader(WithAssetFinder,
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WithNYSETradingDays,
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ZiplineTestCase):
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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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@classmethod
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def init_class_fixtures(cls):
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super(TestPanelDailyBarReader, cls).init_class_fixtures()
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finder = cls.asset_finder
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days = cls.trading_days
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items = finder.retrieve_all(finder.sids)
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major_axis = days
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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 = PanelDailyBarReader(days, cls.panel)
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def test_spot_price(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.spot_price(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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PanelDailyBarReader(unused, transposed)
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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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