|
1
|
|
|
# |
|
2
|
|
|
# Copyright 2014 Quantopian, Inc. |
|
3
|
|
|
# |
|
4
|
|
|
# Licensed under the Apache License, Version 2.0 (the "License"); |
|
5
|
|
|
# you may not use this file except in compliance with the License. |
|
6
|
|
|
# You may obtain a copy of the License at |
|
7
|
|
|
# |
|
8
|
|
|
# http://www.apache.org/licenses/LICENSE-2.0 |
|
9
|
|
|
# |
|
10
|
|
|
# Unless required by applicable law or agreed to in writing, software |
|
11
|
|
|
# distributed under the License is distributed on an "AS IS" BASIS, |
|
12
|
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
|
13
|
|
|
# See the License for the specific language governing permissions and |
|
14
|
|
|
# limitations under the License. |
|
15
|
|
|
import pandas as pd |
|
16
|
|
|
from mock import patch |
|
17
|
|
|
|
|
18
|
|
|
from nose_parameterized import parameterized |
|
19
|
|
|
from six.moves import range |
|
20
|
|
|
from unittest import TestCase |
|
21
|
|
|
from zipline import TradingAlgorithm |
|
22
|
|
|
from zipline.sources.benchmark_source import BenchmarkSource |
|
23
|
|
|
from zipline.test_algorithms import NoopAlgorithm |
|
24
|
|
|
from zipline.utils import factory |
|
25
|
|
|
from zipline.utils.test_utils import FakeDataPortal |
|
26
|
|
|
|
|
27
|
|
|
|
|
28
|
|
|
class BeforeTradingAlgorithm(TradingAlgorithm): |
|
29
|
|
|
def __init__(self, *args, **kwargs): |
|
30
|
|
|
self.before_trading_at = [] |
|
31
|
|
|
super(BeforeTradingAlgorithm, self).__init__(*args, **kwargs) |
|
32
|
|
|
|
|
33
|
|
|
def before_trading_start(self, data): |
|
34
|
|
|
self.before_trading_at.append(self.datetime) |
|
35
|
|
|
|
|
36
|
|
|
def handle_data(self, data): |
|
37
|
|
|
pass |
|
38
|
|
|
|
|
39
|
|
|
|
|
40
|
|
|
FREQUENCIES = {'daily': 0, 'minute': 1} # daily is less frequent than minute |
|
41
|
|
|
|
|
42
|
|
|
|
|
43
|
|
|
class TestTradeSimulation(TestCase): |
|
44
|
|
|
|
|
45
|
|
|
def fake_minutely_benchmark(self, dt): |
|
46
|
|
|
return 0.01 |
|
47
|
|
|
|
|
48
|
|
|
def test_minutely_emissions_generate_performance_stats_for_last_day(self): |
|
49
|
|
|
params = factory.create_simulation_parameters(num_days=1, |
|
50
|
|
|
data_frequency='minute', |
|
51
|
|
|
emission_rate='minute') |
|
52
|
|
|
with patch.object(BenchmarkSource, "get_value", |
|
53
|
|
|
self.fake_minutely_benchmark): |
|
54
|
|
|
algo = NoopAlgorithm(sim_params=params) |
|
55
|
|
|
algo.run(data_portal=FakeDataPortal()) |
|
56
|
|
|
self.assertEqual(algo.perf_tracker.day_count, 1.0) |
|
57
|
|
|
|
|
58
|
|
|
@parameterized.expand([('%s_%s_%s' % (num_days, freq, emission_rate), |
|
59
|
|
|
num_days, freq, emission_rate) |
|
60
|
|
|
for freq in FREQUENCIES |
|
61
|
|
|
for emission_rate in FREQUENCIES |
|
62
|
|
|
for num_days in range(1, 4) |
|
63
|
|
|
if FREQUENCIES[emission_rate] <= FREQUENCIES[freq]]) |
|
64
|
|
|
def test_before_trading_start(self, test_name, num_days, freq, |
|
65
|
|
|
emission_rate): |
|
66
|
|
|
params = factory.create_simulation_parameters( |
|
67
|
|
|
num_days=num_days, data_frequency=freq, |
|
68
|
|
|
emission_rate=emission_rate) |
|
69
|
|
|
|
|
70
|
|
|
def fake_benchmark(self, dt): |
|
71
|
|
|
return 0.01 |
|
72
|
|
|
|
|
73
|
|
|
with patch.object(BenchmarkSource, "get_value", |
|
74
|
|
|
self.fake_minutely_benchmark): |
|
75
|
|
|
algo = BeforeTradingAlgorithm(sim_params=params) |
|
76
|
|
|
algo.run(data_portal=FakeDataPortal()) |
|
77
|
|
|
|
|
78
|
|
|
self.assertEqual(algo.perf_tracker.day_count, num_days) |
|
79
|
|
|
|
|
80
|
|
|
self.assertTrue(params.trading_days.equals( |
|
81
|
|
|
pd.DatetimeIndex(algo.before_trading_at)), |
|
82
|
|
|
"Expected %s but was %s." |
|
83
|
|
|
% (params.trading_days, algo.before_trading_at)) |
|
84
|
|
|
|
quantopian /
zipline
