# # Copyright 2014 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 unittest from collections import deque import numpy as np import pandas as pd import pandas.util.testing as tm from zipline.utils.data import MutableIndexRollingPanel, RollingPanel from zipline.finance.trading import with_environment class TestRollingPanel(unittest.TestCase): @with_environment() def test_alignment(self, env): items = ('a', 'b') sids = (1, 2) dts = env.market_minute_window( env.open_and_closes.market_open[0], 4, ).values rp = RollingPanel(2, items, sids, initial_dates=dts[1:-1]) frame = pd.DataFrame( data=np.arange(4).reshape((2, 2)), columns=sids, index=items, ) nan_arr = np.empty((2, 6)) nan_arr.fill(np.nan) rp.add_frame(dts[-1], frame) cur = rp.get_current() data = np.array((((np.nan, np.nan), (0, 1)), ((np.nan, np.nan), (2, 3))), float) expected = pd.Panel( data, major_axis=dts[2:], minor_axis=sids, items=items, ) expected.major_axis = expected.major_axis.tz_localize('utc') tm.assert_panel_equal( cur, expected, ) rp.extend_back(dts[:-2]) cur = rp.get_current() data = np.array((((np.nan, np.nan), (np.nan, np.nan), (np.nan, np.nan), (0, 1)), ((np.nan, np.nan), (np.nan, np.nan), (np.nan, np.nan), (2, 3))), float) expected = pd.Panel( data, major_axis=dts, minor_axis=sids, items=items, ) expected.major_axis = expected.major_axis.tz_localize('utc') tm.assert_panel_equal( cur, expected, ) class TestMutableIndexRollingPanel(unittest.TestCase): def test_basics(self, window=10): items = ['bar', 'baz', 'foo'] minor = ['A', 'B', 'C', 'D'] rp = MutableIndexRollingPanel(window, items, minor, cap_multiple=2) dates = pd.date_range('2000-01-01', periods=30, tz='utc') major_deque = deque(maxlen=window) frames = {} for i, date in enumerate(dates): frame = pd.DataFrame(np.random.randn(3, 4), index=items, columns=minor) rp.add_frame(date, frame) frames[date] = frame major_deque.append(date) result = rp.get_current() expected = pd.Panel(frames, items=list(major_deque), major_axis=items, minor_axis=minor) tm.assert_panel_equal(result, expected.swapaxes(0, 1)) def test_adding_and_dropping_items(self, n_items=5, n_minor=10, window=10, periods=30): np.random.seed(123) items = deque(range(n_items)) minor = deque(range(n_minor)) expected_items = deque(range(n_items)) expected_minor = deque(range(n_minor)) first_non_existant = max(n_items, n_minor) + 1 # We want to add new columns with random order add_items = np.arange(first_non_existant, first_non_existant + periods) np.random.shuffle(add_items) rp = MutableIndexRollingPanel(window, items, minor, cap_multiple=2) dates = pd.date_range('2000-01-01', periods=periods, tz='utc') frames = {} expected_frames = deque(maxlen=window) expected_dates = deque() for i, (date, add_item) in enumerate(zip(dates, add_items)): frame = pd.DataFrame(np.random.randn(n_items, n_minor), index=items, columns=minor) if i >= window: # Old labels and dates should start to get dropped at every # call del frames[expected_dates.popleft()] expected_minor.popleft() expected_items.popleft() expected_frames.append(frame) expected_dates.append(date) rp.add_frame(date, frame) frames[date] = frame result = rp.get_current() np.testing.assert_array_equal(sorted(result.minor_axis.values), sorted(expected_minor)) np.testing.assert_array_equal(sorted(result.items.values), sorted(expected_items)) tm.assert_frame_equal(frame.T, result.ix[frame.index, -1, frame.columns]) expected_result = pd.Panel(frames).swapaxes(0, 1) tm.assert_panel_equal(expected_result, result) # Insert new items minor.popleft() minor.append(add_item) items.popleft() items.append(add_item) expected_minor.append(add_item) expected_items.append(add_item)