mirror of
https://github.com/wassname/catalyst.git
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Jean Bredeche
b1428aaad1
Removed it from ExchangeCalendar. Fixed TradingSchedule’s implementation to be much faster. Removed the `step` parameter.
110 lines
3.6 KiB
Python
110 lines
3.6 KiB
Python
from unittest import TestCase
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from pandas import (
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Timestamp,
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date_range,
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DatetimeIndex
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)
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import numpy as np
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from zipline.utils.calendars import (
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get_calendar,
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ExchangeTradingSchedule,
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normalize_date,
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)
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class TestExchangeTradingSchedule(TestCase):
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@classmethod
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def setUpClass(cls):
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cls.nyse_cal = get_calendar('NYSE')
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cls.nyse_exchange_schedule = ExchangeTradingSchedule(cal=cls.nyse_cal)
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def test_nyse_data_availability_time(self):
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"""
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Ensure that the NYSE schedule's data availability time is the market
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open.
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"""
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# This is a time on the day after Thanksgiving when the market was open
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test_dt = Timestamp('11/23/2012 11:00AM', tz='EST')
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test_date = normalize_date(test_dt)
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desired_data_time = Timestamp('11/23/2012 9:31AM', tz='EST')
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# Get the data availability time from the NYSE schedule
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data_time = self.nyse_exchange_schedule.data_availability_time(
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date=test_date
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)
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# Check the schedule answer against the hard-coded answer
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self.assertEqual(data_time, desired_data_time,
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"Data availability time is not the market open")
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def test_nyse_execution_time(self):
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"""
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Runs a series of times through both the NYSE calendar and NYSE
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schedule, ensuring that the schedule and calendar agree.
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"""
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# Get all of the minutes in a 24-hour day
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start_range = Timestamp('11/23/2012 12:00AM', tz='EST')
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end_range = Timestamp('11/23/2012 11:59PM', tz='EST')
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time_range = date_range(start_range, end_range, freq='Min')
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for dt in time_range:
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cal_open = self.nyse_cal.is_open_on_minute(dt)
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sched_exec = self.nyse_exchange_schedule.is_executing_on_minute(dt)
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self.assertEqual(
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cal_open, sched_exec,
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"Mismatch between schedule: %s and calendar: %s at time %s"
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% (cal_open, sched_exec, dt)
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)
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def test_execution_minute_window_forward(self):
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dt = Timestamp("11/23/2016 15:00", tz='EST').tz_convert("UTC")
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# 61 minutes left on 11/23, closed 11/24, only 210 minutes on 11/25
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minutes = self.nyse_exchange_schedule.execution_minute_window(dt, 300)
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np.testing.assert_array_equal(
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minutes[0:61],
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DatetimeIndex(
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start=Timestamp("2016-11-23 20:00", tz='UTC'),
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end=Timestamp("2016-11-23 21:00", tz='UTC'),
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freq="min"
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)
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)
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np.testing.assert_array_equal(
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minutes[61:271],
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DatetimeIndex(
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start=Timestamp("2016-11-25 14:31", tz='UTC'),
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end=Timestamp("2016-11-25 18:00", tz='UTC'),
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freq="min"
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)
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)
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np.testing.assert_array_equal(
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minutes[271:],
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DatetimeIndex(
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start=Timestamp("2016-11-28 14:31", tz='UTC'),
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end=Timestamp("2016-11-28 14:59", tz='UTC'),
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freq="min"
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)
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)
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def test_execution_minute_window_backward(self):
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end_dt = Timestamp("2016-11-28 14:59", tz='UTC')
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start_dt = Timestamp("2016-11-23 20:00", tz='UTC')
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from_end_minutes = \
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self.nyse_exchange_schedule.execution_minute_window(end_dt, -300)
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from_start_minutes = \
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self.nyse_exchange_schedule.execution_minute_window(start_dt, 300)
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np.testing.assert_array_equal(
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from_end_minutes,
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from_start_minutes
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)
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